{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Notebook to test `MyLinearRegression` class and its methods\n",
    "### Dr. Tirthajyoti Sarkar, Fremont, CA 94536"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from MyLinearRegression import MyLinearRegression as mlr\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Generate random data with noise"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "num_samples=40\n",
    "num_dim = 5\n",
    "X = 10*np.random.random(size=(num_samples,num_dim))\n",
    "coeff = np.array([2,-3.5,1.2,4.1,-2.5])\n",
    "y = np.dot(coeff,X.T)+10*np.random.randn(num_samples)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Instantiate a model object (we imported the class as `mlr`)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "model = mlr()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### What if we just print the model?\n",
    "The `__repr__` method should kick in"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "I am a Linear Regression model!"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Ingest the data by invoking the `ingest_data` method"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "model.ingest_data(X,y)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### In theory, you can reach inside the model and look at the class variables like `features_`.\n",
    "This is, however, not recommended. The idea of Object-oriented programming is to separate core functions from the user API. Only use the high-level linear-regression related API functions like `fit`, `predict`, or `histogram_resid`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[5.14756341, 4.4695061 , 3.47104456, 9.40286684, 4.41800273],\n",
       "       [1.07539458, 4.21655694, 1.44855154, 8.49167788, 1.71239689],\n",
       "       [4.11686871, 9.20815826, 8.91247482, 1.76354031, 1.50853858],\n",
       "       [3.27190154, 3.20772777, 0.93022954, 0.84110261, 9.29072503],\n",
       "       [7.58228104, 9.91076151, 6.94014864, 1.11787281, 4.9943318 ],\n",
       "       [8.59882292, 8.85728508, 7.40445246, 7.36960121, 0.83286588],\n",
       "       [9.2730149 , 2.18713816, 9.18467117, 0.40380755, 7.00943527],\n",
       "       [5.39352199, 9.65383703, 2.06523596, 2.43322619, 9.34616696],\n",
       "       [3.85012151, 6.91824923, 6.69921042, 0.51970335, 6.1432167 ],\n",
       "       [4.29064881, 1.83271943, 8.67760011, 7.44045372, 0.46499688]])"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.features_[:10]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Try printing out linear regression parameters like $R^2$ and MSE.\n",
    "Wait, the model has ingested the data but has not been fitted yet i.e. we have not called the fit method on it. We expect the class to handle this gracefully and print out a message to the user if she calls these methods without first fitting the model."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model not fitted yet!\n",
      "R-squared:  None\n",
      "Model not fitted yet!\n",
      "Adjusted R-squared:  None\n",
      "Model not fitted yet!\n",
      "MSE:  None\n"
     ]
    }
   ],
   "source": [
    "print (\"R-squared: \",model.r_squared())\n",
    "print (\"Adjusted R-squared: \",model.adj_r_squared())\n",
    "print(\"MSE: \",model.mse())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Fit the model with `fit`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "model.fit()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Print the same parameters as above"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "R-squared:  0.8402589251315261\n",
      "Adjusted R-squared:  0.8167675905920446\n",
      "MSE:  59.473869215821594\n"
     ]
    }
   ],
   "source": [
    "print (\"R-squared: \",model.r_squared())\n",
    "print (\"Adjusted R-squared: \",model.adj_r_squared())\n",
    "print(\"MSE: \",model.mse())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Inference related parameters - p-values, t-test values, and standard errors"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "P-values: [1.47986697e-01 3.78869092e-05 2.67723112e-08 2.77571333e-01\n",
      " 1.68733877e-11 2.59990525e-02]\n",
      "t-test values: [-1.48035344  4.73415209 -7.17593129  1.10347199  9.85639767 -2.32797349]\n",
      "Standard errors: [5.60655056 0.52991369 0.49773764 0.42776842 0.45672968 0.5150272 ]\n"
     ]
    }
   ],
   "source": [
    "print(\"P-values:\",model.pvalues())\n",
    "print(\"t-test values:\",model.tvalues())\n",
    "print(\"Standard errors:\",model.std_err())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Fitted vs. residuals plot (to check for linearity and homoscadasticity)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "model.fitted_vs_residual()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Fitted values vs. feature variables"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x504 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "model.fitted_vs_features()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Pairplot of the dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "This may take a little time. Have patience...\n"
     ]
    },
    {
     "data": {
      "image/png": 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qruyx4SPi1V8+5wtxAx9kmSOxxzTr54AAtGZTV+5ra82msgz2XJWK0djIkA7smWCfOvpW9vwjn7ore2z4iHj1l8/5QtzAB1nmSOwxzUoMIACxz6bmobUHr2KWPkdStFE88o986obY8BPx6iff84W4gWtZ50jMMe3t2wTGmH8h6YuS3i3JSvoNa+0Rt60C3Ih9NhXwGfmHbogNIDnyBVgbOZKczysx7pX0NWvtT0p6j6RnHbcHcCrm2VTXmk2r6dkFNe3SZ54LjzbkX2fkTraxQX8iRivjuj6/9EsZtRQRyKNmc7+RjJcrMYwxF0h6v6RfkyRr7ZykOZdtAhAnHpEI9IbcyRb9iRgR14gVse2Wrysxtkg6I+nPjDHHjDFfNMaMuG4UEBve9fP7kW9lR3z6jdzp38oYn5lboD+xrtDqInUCscoztkPLcxd8ncQYkPTTkv7QWrtT0oyk21f+A2PM9caYSWPM5JkzZ1y0EUjNp7htzSDvPTipS+94VHsPTur1N+c1/WZ/RTO0wuvzI9984CpmO8Xn1Myc9/HkoyQ52Uve+po7ecVs1rWtFeN/+v+e0vOvTGtkeMDL/kQxksRtiHXR1zrRTRZ5Htp9UK98uqd1oTZU1UUXDOuxm96vf/q9j+qxm96viy4Y7ju2Q8xzF3ydxPihpB9aa59c+vNfanFSY5m19j5r7YS1dmLTpk2FNxDohU9x2z6DvOn8Yb0+u6C99/deNEMsvK3HWa3UepwV3MUs795lI0lO9pq3vuZOHjGbR22rzzd06Mkf6Jd3vkN3Hn5Gz78y7WV/ohhJ4jbEuuhrnegkizwP8T6oVz7d07rw5nxDt3xkm+48/Iy2feZR3Xn4Gd3ykW16Y67R99gQWp674OUkhrX2v0t60RizbelLH5L0XYdNAqLT/u7IDZdv1a0PnuiraIZYeH1/5FtZhfbuna+S5GSveVum3MmjttWGqvrIu9+m2x5arLtf+OZJfe7j20vRn+hNiHUxpDqRRZ6HeB+E3jSbOue++dYHT+hHb8z3PTaElucueHmw55J/J+krxpghSack/brj9gBRab07cuTUlCRp64WjfRdN3wtvs7l0MnrbY6t4nJV/Vsbn1e+5WDdcvlVbLxzVzOyCRoY4rTupJDnZa97Gnjsr60Ueta0+11hVdw8/9ZIk6c6r36VLLhqNrj/Rv/ZxW/rxqobR4XS39N3Gw6yFVCeyyHPf74PKoKjYrg13vtYXXrBBpo8fl2Wex8zLlRiSZK09vrREabu19pettf/DdZuAmLS/O/Li2XrfSz59Xja61hJPHmfln1Z83nzFJbrlF368XPP6+78d7dLcPCTJyX7yNtbcaa8XL0z1Xx/b1QarmpldWPV9Dz/1ku48/MzyzWos/YlsZLWqoegtD6HUiSzuYXy+DyqDImO727V+8Wy977EhlNVLLnk7iQEgXyvfHXnus7+oCy8Y1v7dO/oqmj4XXpZ4hqUVn7/+v//E8nJ7rlt6SXLS57x1pb1e3PP4c7r7mmy3elQqRiNDVd3bZ91FebSP2wf2TPT0OEfGw86yqIXUU7eKjO3Fa726ft99zXa9pTbY99iQRZ7HjjUpQIm13h2RpNrQgDYMVPta8unzslGfl3g2Gk3V5xsaGR7QzOyCaoNVVavhzTFnvYSzUjFrPrGhaa1XMeajJDnpc9660l4vDj/1kipGOnDdhGrD2fWRWXpnevn7zi7mT+h9X9Ry7jJaOW73urTc5/EwD0njMYta2O/3KEPu5Pka84rt7tuRh1fV70pF2jDQ/+vJIs9jR69kbPz2R1w3oRTS9vPpu67KqSVxyaJo+lp4fd1j2Gg0NTUzpxsfOK6jp89q1/hG3XvtDo2NDAU1kdFawrnv0LHl17F/986+3z3odt1emKrrinv+NrOfE7MkOelr3rrSKe5e+dGsZLS8JL5f3XIm9F8k86oFyI6v42Ee0sajy/ugMuRO3q8xj9her82jG5au9Ya4csd34dwhA0AffF3iWZ9v6MYHjq9a+njjA8eDW9ab1xLOTtft7mu2657Hn2MZNHJTRL2IdUl/rK8rJr6Oh3kIKR5Damuv8n6NecR2Ga5LiPqeMjLG/KSkj0l6uyQr6SVJh621z/b7vQGEz5elkb4ume+2XWIksHfD8lrCec51m23oM3/19PKTHPr5Ob7EJvxTRL2IdUl/KK+rzPnv63iYxzUJJR6lsNraq7xfYx6xXYbr0gvXNbSvlRjGmNskPSDJSPoHSUeX/vuQMeb2/psHIGRFn4C+Hh9PSG9/OoG0uPRxZnbBUYt6k+eJ7Cuvm8zSsv4+f45vsQn/5F0vYn2KQQivi/z3bzzM65qEEI8tIbW1V0W8xqxjuwzXJS0fami/20k+JWmXtfYua+2Xlz7ukvQzS38HoMRYgre+2mBV9167+nTre6/dEdyy3qKWJ2f1c4hNuBbrkv4QXhf5758ityT6Fo8tIbW1VyG+xhDbnDcfami/65Wbki6W9IO2r79t6e8A5Mz1cq61sARvfdVqRWMjQ7rvuvcG/XSSopYnZ/Vzij7BHGjn65L+bop8wkPeGJv8Uxuq6qILhvXYTe/X1gtHdfLVaf3ht05mvyXRw3hsCamtvQrxNYbY5n4kqfU+1NB+JzFukvR1Y8zzkl5c+tpmSVsl/Xaf3xvAOnw/ybpMJ6D3o1qt6PylSYvzNww6bk3vinrCRRY/x8UJ5kC7UJ4K4+IJD3libPLPm/MN3fKRbbr1wRPLMXb3Ndv15nxDtaH+ronv8bhSSG3tVYivMcQ29yJprfehhvb1Vp+19muSLpX0nyQ9JulvJN0padvS3wHIkQ/LudbCEjz4ihPMgeRii23GJv80m9KtD55YFWO3PnhCTdZ1A4VJWut9qKF9T5VYa5uS/r8M2gIgJR+Wc62lbEvwEA5OMAeSiy22GZv8UxvuEmPDYcYYEKKktd6HGhrWpmsAq4RwYrJvJ6ADLZxgDiQTY2wzNvklxhgDQpMmD13XUCYxgID5sJwLwCLyEbEitpE3YgxwL6Q8jPdkEqAEfFjOBWAR+YhYEdvIGzEGuBdSHjKJAQSuLCcmAyEgHxErYht5I8YA90LJQ7aTACXUbFpNzy6oaZc+N63rJgFeIDeA4pF3iB0xjiSIk+T8nV4BkFqzaVWfb6y5BCzpM6CBsilzbiSpHUAeOufdDo0MD2jDAHHYDTkbjjKPLUgubZyUvQawEgOIRKv47T04qUvveFR7D05qambunFncpM+ABsqmrLmRtHYAeeicd8f16o9micMuyNmwlHVsQTpp4oQaULKVGOO3P5L6/zl911U5tATI3sriJ2m5+B3YM7FqT1vSZ0AjO2WfLQ/FWrkxPbsQ7fVLWjuAtJLUvm55986NNX3ii08Shx2EnLNlHA+57wqHy/hMEych14CssBIDiETS4sez2IvVebZ8VvU59jr6pltuTL+5EPW7HetN3sT0WotU9r3NiVcHdsm7k69O84teF/38UuwyLsv67jH3XfnIOpZdx2eaOGFizONJDGNM1RhzzBjzX123BQhB0uIX0jOgY8BS6XB0yo17d+/Ql/7b96NeBtytdjz/ynRpfsnImuubYR8kXRrdKe8+9/Ht+sI3T/KLXhe9/lLsOi7Luq2C+67s5RHLruMzTZwwMeb3dpIbJT0r6QLXDQFC0Cp+7QcCtRe/kJ4BHQOWSoejU26cN1jR/m+cXPXvYnu3o1Pt+NzHt+sP/uZ7pVyimgWW+iZ/p3A5766bUG24qhem6rrn8e/pzOuz/KLXRdLxvp3ruCzru8fcd2Uvj1h2HZ9p4qTXGhATL0dSY8w7JF0l6bOSbnbcHCAIaYpfKM+AjkFrtrw10EoslfZZe25Mzy50vH71uUY0udNeO55/ZVp/8Dff0+GnXpJUjl8ysub6ZtgH3Wpfp9ypVIxGNwyo2bR66/nDuudXd/CL3hp6/aXYdVymiYnYcN+VrTxi2Yf4TBonTIz5u53k85J+R1Kz2z8wxlxvjJk0xkyeOXOmuJYBfcg7blvFr2KWPpeomK3H1T7g0JdKl73Wul4GXFTctmpHfa6hOw8/szyBIYW3RDWLmO2331nq21vulHkMSxu3vfSV67h0VU/Lfj5NXlzeH9TnGtr3wa167Kb3659+76N67Kb3a98Ht/YVy67H+7TKXC8lyVjrVyIbY35J0kettf+3MeYDkm6x1v7SWv/PxMSEnZycXPd7F/F0kl5+Ri96eWpK2rb5/GSWHF9LYRUgadyif66f0d5s2sVZ8qWl0p9/4jm98qPZrNpAzObM1WnlLuK2wJ9ZSNz2ErNZ9IHrmuOLyJ5EEXyt9SEui44JH16zQ8HHbDeNRlNTM3O68YHjy9f13mt3aGxkSNVq7+/RR1azQpWow31cz/Rzkq42xnxU0gZJFxhjvmyt/YTjdgEIlOt9wCyVDpurZcAu4pYlqtn0O/24iCX0fvEhLouOCdfjP/LxxkJTNz5wfNV1vfGB44vXtY9JDGpWOLzbTmKt/bS19h3W2nFJ10r6BhMYAPrheh9wS9mX/iEdV3Fb9jjNqt/L3o/wU9ni0pfxH9niusK7SQwAyJrrfcDsx0UvksYt8ZUt1/Wi7Ihnt2Lrf/I5TrFe19jyL09eT2JYa7+13nkYAMLiokC7PKwpj2eZoxySxK3L+Ir1Ziu0w918ljZGqJduxdj/ReRzrLXQZ6HV6SQxEmP+5YnNPgAK4+qALZf7gNmPi14liVtX8RXzYXk+nBsQg15ihHrpVoz9n3c+x1wLfRZSnU4aIzHmX568XokBIC4rC/RC0y4X6Pp8/sv/XO0DZt8m+rFe3LqKL5e5XISynRuQh15ihHrpVqz9n2c+x14LfRZKnU4aI7HmX16YxADQUR7LI8tYoGPdt9kvlt9mw1V8lS2Xidf0eokR6qVb9H96WdZC6kz2fOjTpDFC/qXDJAaAc+S1L6+MBTq0fZtFYN9ndlzFV5lymXjtTS8xQr10i/5PL6taSJ3Jni99mjRGyL90mMQAcI68lkeWsUCv3Lf53Gd/UQf2TJR+ryzLb7PjKr7KlMvEa296iRHqpVv0f3pZ1ULqTPZ86dOkMUL+pcMpIYEav/2RKH6GJJ2+66pCfg6Sy2upeEgHMWWptW9TEoczqXxbEfLmIr7KlMvEa296jRHqpVv0fzpZ1ULqTPZ86dM0MUL+JcdKDADnyHOpeCgHMSE/ZdqKELOy5DLx2ruyxAjKLYs4p85kz6c+pRZmj0kMAOco01JxFI/4QkiIVwB5o85kjz6NG+tUAJyjTEvFUTziCyEhXgHkjTqTPfo0bkxiAOiIfXnIE/GFkBCvAPJGnckefRovtpMAcKb9+d2NRtP587yRLx+e2Y7scV3dCaHvQ2hjjELr99DaC0jcy7rClBQAJ1rP79536JiOnj6rfR/cqmt/ZrNufOC4jp4+q13jG7V/986eHy/VbFrV5xssIfRI+zVfvMY7NDI8oA0DXJ9Qdb6uvedumfRbp0Lo+xDaGKMQ+n1V/M821Gg29W+//I/ethe9i/WeLO97WXTHSgwATrQ/v/sj736bbnzgeCbP824NKnsPTurSOx7V3oOTmpqZYzbcsc7PbD+uV380y/UJWOfr2lvulkkWdSqEvg+hjTHyvd/Pif/7J/X67II2nT/sZXvRu5jvyfK8l8XamMQA4ET787u3Xjia2fO8fb95K6tuz2x/58Ya1ydg3a5rL7lbJlnUqRD6PoQ2xsj3fu8U/7c+eEI3XL51+d/41F70LuZ7sjzvZbE2JjEAZCbNftb253effHU6s+d5+37zVlbdntl+8tVpr68P+7TX1u269pK7ZZJFnQqh74toIzl6rqz6Pa++7Rb/Wy8c7au98E/M92R53su65ntdZRIDCJCPhSXtcsH253c/9p2Xde+1OzJ5nncIN/Zl1OmZ7Z/7+HZ94Zsnvb0+Pi+D9aUOdLquveZu0Vz2YRZ1KoS+z7uNPueoS1n0e5592y3+XzxbX9HeHaoYlf5ahi7me7Jk97I7vKrJSYRQV421/jSmVxMTE3ZycnLdfzd++yOpv/fpu65K9e97+Rlll7aPpfT9nOJnFHbqTtK4befrYV3Tswvae3BSR05NLX/tsi1jOrBnoutjrdoPejq3Y6igAAAgAElEQVRvoKI3Fpp9H/zkax/lxPuYXanZtIvXdriqF6bq+vwTz+mVH816e316iesi+BbjPRzaVkgj14pZ132Y1c8P4cC8PNtYYI4GVWul/vs9z77tetDz0IA2DIUxPgTAi5h1XWvz1n5ArWT12vSc3rmxphfP1vWW2qDO3zAY1Gt1fO+TqKN4OgkQmJV7CyUt7y10/UtVL8sFOz2/e7RaWfXnXlQqRmMjQzqwZ8LrG/syqlSMRjcMqNm0euv5w7rnV3d4fX18XQbrWx3olMu+c92HWdWpEPo+zzb6mqM+6Lff8+zbbvFfn2/o3xx4ctUvTz7c46B3sd+TrcwzGWnvwW9798ZHWiHUVbaTAIHxtbD4tlywNahUzNLnSAbLWIRyfXyL6xZf60BIfOjDUPLAZ77maAzy7ttO8e9DXiJ7Zal1scRvCHXVy0kMY8w7jTHfNMY8a4x5xhhzo+s2Ab7wtbCEsDcbSMvXuPa1DoSEPoyDrzkaAxd9S14iZLHEbwh11dd1LQuS/oO19h+NMedL+rYx5nFr7XddNwxwrVVY2vcWui4ssS8XRDn5Gte+1oGQ0Idx8DVHY+Cib8lLhCyW+A2hrno5iWGtfVnSy0v//box5llJb5dU+CQGB3Xmjz5Ox+fCEsLebCAtH+Pa5zoQCvowHj7maCyK7lvyEiGLKX59r6v+taiNMWZc0k5JT7ptCeAP3wsLgPxRB/pHHwL+IS8RMuK3GF6eidFijBmV9JCkm6y1P2r7u+uNMZPGmMkzZ864aSCQEnGL0BCzCA0xixARtwgNMQuXvJ3EMMYManEC4yvW2ofb/95ae5+1dsJaO7Fp06biGwj0gLhFaIhZhIaYRYiIW4SGmIVLXk5iGGOMpD+R9Ky19h7X7QGK1mxaTc8uqGmXPjet6yYBKAC5jxAQp4Ab5F68uLbp+LpR5+ckfVLS08aY40tf+4/W2q86bBNQiGbTampm7pyTjcdGhoI8GAhAMuQ+QkCcAm6Qe/Hi2qbn5UoMa+3fW2uNtXa7tXbH0gcTGCiF+nxD+w4d05FTU1poWh05NaV9h46pPh/WM6YBpEPuIwTEKeAGuRcvrm16Xk5iAGVWG6rq6Omzq7529PRZ1YbCesY01sfSwXOVuU/I/XAQp8Rp2ZU5B1wpW+6VKcbKdm2zwCQG4Jn6XEO7xjeu+tqu8Y2qzzEbG5PW0sG9Byd16R2Pau/BSU3NzEU9SK+n7H1C7oeBOCVOy67sOeBKmXKvbDFWpmubFSYxAM/UBqvav3unLtsypoGK0WVbxrR/907VBpmNjQlLB89V9j4h98NAnBKnZVf2HHClTLlXthgr07XNiq8HewKlVakYjY0M6cCeCdWGqqrPNVQbrHKwT2RYOniusvcJuR8G4pQ4Lbuy54ArZcq9ssVYma5tVliJAXioUjEaHR5QxSx9pohFh6WD56JPyP0QEKfEadmRA+6UJffKGGNlubZZYRIDQKbKdBBTP1g6eK5OfXLv7h06b4ChCv4gd/3E2JNer31GDiBvscQYdSk/bCcBkBmec50cSwfPVakYbawN6o8/+V6NDA/o5KvTeuDJF7T7ff+SGII3yF3/MPak10+fkQPIWwwxRl3KF29vAchM2Q5i6hdLB8/1xkJTv/Xn39b/8h+/qo98/u90zxPPE0PwDrnrF8ae9PrtM3IAeQs9xqhL+WISAyiJIpa0le0gJmQvthhiKSnKwmWsx1Y3ikCf5Ye6D6mYHCtzrDGJAZRAUc/bLuNBTMhWTDFUtufco7xcx3pMdaMo9Fk+XOcC/JF3jpU91pjEAEqgqCVtsRzEBHdiiiGWkqIsXMd6THWjKPRZPlznAvyRd46VPdY42BMogaKWjcZwEBPciimGWK6NsnAd6zHVjaLQZ/lwnQvwR945VvZYYyUGUAJFLhsN/SAmuBdLDLFcG2XhQ6zHUjeKRJ9lz4dcgD/yzLGyxxqTGEAk1jrch2WjQPFCz7syHxiWpxj7NfRYB7LSLRfOG6hEl/d5i7FWZqnsdZftJEAE1nsWNctGgeKFnHc83z4fsfZryLEOZKlTLpw3UNHZ+nx0eZ+nWGtllsped1mJAUQgyeE+LBsFihdq3pX9wLC8xNyvocY6kLX2XHhjoRlt3ucl5lqZpTLXXSYxgAiU/XAfANmipuSDfgXKh7xPjz7DepjEACJQ9sN9AGSLmpIP+hUoH/I+PfoM62ESA4hA2Q/3AZAtako+6FegfMj79OgzrMfbgz2NMVdKuldSVdIXrbV3OW4S4K2yH+4DIFvUlHzQr0D5kPfp0WdYj5eTGMaYqqQvSPqwpB9KOmqMOWyt/a7blgH+ah3uI2n5MwD0ipqSD/oVKB/yPj36DGvxdTvJz0g6aa09Za2dk/SApI85bhMAAAAAAHDI10mMt0t6ccWff7j0NQAAAAAAUFK+TmJ02vBkV/0DY643xkwaYybPnDlTULOA/hC3CA0xi9AQswgRcYvQELNwyddJjB9KeueKP79D0ksr/4G19j5r7YS1dmLTpk2FNg7oFXGL0BCzCA0xixARtwgNMQuXfJ3EOCrpEmPMTxhjhiRdK+mw4zYBAAAAAACHjLV2/X/lgDHmo5I+r8VHrP6ptfaza/zbM5J+sPTHt0p6Lf8WBoG+WC1Jf7xmrb2yiMa0xW3ZEavdrdc3vsUs15I+8KbWErM9oT9Wa/WH61rLdVlEPyzyps5Kud7Thni9aXN/EsWtt5MYvTLGTFprJ1y3wwf0xWr0h7+4Nt2F1jehtTcPZe+D0F5/aO3NG/2xmi/94Us7XKMfFpWlH0J8nbS5GL5uJwEAAAAAAFiFSQwAAAAAABCEGCcx7nPdAI/QF6vRH/7i2nQXWt+E1t48lL0PQnv9obU3b/THar70hy/tcI1+WFSWfgjxddLmAkR3JgYAAAAAAIhTjCsxAAAAAABAhJjEAAAAAAAAQWASAwAAAAAABIFJDAAAAAAAEAQmMQAAAAAAQBCYxAAAAAAAAEFgEgMAAAAAAASBSQwAAAAAABAEJjEAAAAAAEAQmMQAAAAAAABBYBIDAAAAAAAEgUkMAAAAAAAQBCYxAAAAAABAEJjEAAAAAAAAQYhiEuPKK6+0kvjgI4uPwhC3fGT0URhilo8MPwpBzPKR4UdhiFs+MvooDDHLR4YfiUQxifHaa6+5bgKQGnGL0BCzCA0xixARtwgNMYuiRTGJAQAAAAAA4sckBgAAAAAACAKTGAAAAAAAIAhOJzGMMX9qjHnVGPOdFV/baIx53Bjz/NLnt7hsIwAAAAAA8IPrlRhfknRl29dul/R1a+0lkr6+9GcAAAAAAFByTicxrLV/J+ls25c/Jung0n8flPTLhTYKmWo2raZnF9S0S5+biZ+cAwBYgXrqD64FUCxyLnxcQ2RpwHUDOrjIWvuyJFlrXzbGXOi6QehNs2k1NTOnfYeO6ejps9o1vlH7d+/U2MiQKhXjunkAEAzqqT+4FkCxyLnwcQ2RNdfbSXpmjLneGDNpjJk8c+aM6+agg/p8Q/sOHdORU1NaaFodOTWlfYeOqT7fcN00Z4hbhIaY9QP1NLm8Y5ZrgTxQa7sj5/yUJma5hsiaj5MYrxhj3iZJS59f7fSPrLX3WWsnrLUTmzZtKrSBSKY2VNXR06t3Cx09fVa1oaqjFrlH3CI0xKwfqKfJ5R2zXAvkgVrbHTnnpzQxyzVE1nycxDgsac/Sf++R9NcO2xKVRqOp19+cV9Navf7mvBqNZq4/rz7X0K7xjau+tmt8o+pzzLoCMSpqv2sZ99VST/2R5bWINZZjfV1wo9+cCykeQ2prGiuv4dXvuViP3fR+fe//+UXNBPIaY70uIXP9iNVDko5I2maM+aEx5lOS7pL0YWPM85I+vPRn9KnRaGpqZk7X3/9tXXrHo7r+/m9ramYu14mM2mBV+3fv1GVbxjRQMbpsy5j2796p2mBxs64UHaAYrf2uew9O6tI7HtXeg5OampnLPOeS/pzYct+HeopFWV2LXnImhLguqhagNyHEULt+ci6keAyprWm1ruHNV1yiW35hm+48/Iy2febHv4/49hpX5kl9bkFTM7NRXpeQGWvDvwATExN2cnIys+/XbFrV5xuqDVVVn2uoNlgN/tCZ19+c1/X3f1tHTk0tf+2yLWO677r36vwNg7n9XJd92eMhQoVd6KzjFqXlRcxOzy5o78HJc2rMgT0TGh1Ofob0ejUjyc+J9QCxyMamQhqeV51tNJqqzzc0MjygmdkF1QarqlbTvS+UNmdCieusaoGHvKi1/cgyhoquR73+vJDiMYe2ehWzzabVzNxCx99HOr1GV2Nee548cfPP69MPPx1EDEUi0UX2cTuJU7HOgo4MD3TcizaSc/JVKkajwwOqmKXPBd5ocYgQUJws9rsmqb9Jfk6sue+ynuLHmk2rs/X5VSsbz9bnU98npM2ZUOKave/+yiqGXNwr91r/QorHkNrai0rFdP19pP01uvx9rD1P3rmxFvV1CRWTGG1CuUlIa2Z2oeN+wpnZBUctyl/sgwHgkyzOCUhSf5P8HHIfecrqPiFtzoQS15zf4q+sYiike+WQ4jGktvYq6Wt0GWPteXLy1enor0uImMRoE8pNQlq1waruvXbHqv2E9167I+r91GUYDABfZHFOQJL6m+TnkPvIU1b3CWlzJpS45vwWf2UVQyHdK4cUjyG1tVdJX6PLGGvPky9886TuvmZ71NclRGzkadMK3JX7nloFPuR9T9VqRWMjQ7rvuvf2tYc3JK1C2b73k6IDZK9SMRobGdKBPRM9719NUn+T/BxyH3nK6j4hbc6EEtdZ1ALkI6sYCuleOaR4DKmtvUr6Gl3GWHuenHl9VucPD+jAdROqDcd5XULEwZ5tfDw4K7LD3ArVQ995dQgSkEA0MRvyoXMxKajvgj3YM2mc5tGPxLVTUdTaLA6l9fFeGR0FG7NJYizPekitdSpRR/s1XeoB32ZBGSj60zoISpJ37w4AWC3L+kvu94YxZ31J4jSvfiSu0Y/WobT9xqVv98qIz3oxlvdYRa31X7x7Cfrg4gT4bs/tbh1ss+n8YT2y71/ry7/5Ps3MLujNBb/2wAJAFnx8Ake3+uyLLNsX0oF9Lq0Xp/Tjol5i0/d8C1mSuEza/73Waq4vklorxvKqsa7j0/XPDwlTSx5YazaxNlTVRRcM6+YPb9NtD51Y8fc7tGGAWW8AyJPvKxOybl9IB/b5jH7sLTZ9z7fQrReXefc/1xdZyaPGuo5P1z8/NKzE8MBas4n1uYZuuuJS3fbQiba/P166d3QAoGi+v6OedftCeQKG7+jH3mLT93wL3XpxmXf/c32RlTxqrOv4dP3zQ8MkhgfWmk2sDVa1eaxWund0WE4FwAe+v6OedfvK8Ii/ItCP6WOz2bTe55vv1rt3Wi8u8+5/ri+ykkeNdR2frn9+aL97sZ3EA+s9Rmj6zYVgHmWVBZZTIUbjtz+S+v85fddVObQEafj+KMH6bJf2zTY0uiF9+ziwLxv0Y7rcaY37M7Plut/JUpJ7p/XiMu9653s9RTjyqLGu49Plzw/xdy9WYnggycx4yO/opJ3ZYzkVAF/4/o76QEX6o0++V//0ex/VYze9XzdfcYnuvma7Kn2M7j4erhqisvVj+1h/3kAlce60xv17Hn9On/v4dm/zzWdJ753Wisu8610/3z+0d4mRv6xrrOvxfuXP/+UdF+tbt3xAX9n7Pskq93gP8Xcvpj09sN5sYsjv6PQys+d6ORUAtPhcf5tNq9dnF7Tv0PHl+vr5a3foa995WZ+8bNx181Ai3cb6jbXBRLnTGvcXlm7U77z6Xdp64ajemGuoNuRHvvkui3unvOtdr98/xHeJER7X433r5//Jr01opm1szzveQ/zdi5UYnlhvNjHUd3R6OtiLA9EAeMTX+rtYX4+vqq83PXBcP3/phdRLFKrbWP/GQjNR7qwc9w8/9ZI+8vm/0ye++KRk5E2++S6re6e8610v3z/Ed4kRJtfjfaVi1LQ6Z2zPO95D/N2LSQzkqpeZPdfLuQAgBN3q6+axGvUSher3XTzG/f7F3IchvksM9MpFvIdYP9hOglz1ckiN6+VcABCCrvW1x0M9gV71eyAd437/Yu5D1wcuAkVyEe8h1g9WYiBXvc7suV7OBQC+61pfeXcSBcviXTzG/f7F2ochvksM9MpVvIdWP5i+RK5CnNkDgBBQX+ELYhF5Ir5QJsR7MkxiIHetmT1JLPsDgAxRX+ELYhF5Ir5QJsT7+thOAgAAAAAAgsAkBgAAAAAACIK3kxjGmH9vjHnGGPMdY8whY8wG120CAAAAAADueDmJYYx5u6R9kiaste+WVJV0rdtWAQAAAAAAl7ycxFgyIOk8Y8yApJqklxy3BwAAAAAAOOTlJIa19p8l/YGkFyS9LOl/Wmv/xm2rAAAAAACAS15OYhhj3iLpY5J+QtLFkkaMMZ9o+zfXG2MmjTGTZ86ccdFMIDXiFqEhZhEaYhYhIm4RGmIWLnk5iSHpCknft9aesdbOS3pY0r9a+Q+stfdZayestRObNm1y0kggLeIWoSFmERpiFiEibhEaYhYu+TqJ8YKknzXG1IwxRtKHJD3ruE0AAAAAAMAhLycxrLVPSvpLSf8o6WkttvM+p40CAAAAAABODbhuQDfW2t+V9Luu2wEAAAAAAPzg5UoMAAAAAACAdkxiYFmzaTU9u6CmXfrctK6bBADwGONGtuhPxIi4RqyIbXeYxICkxSScmpnT3oOTuvSOR7X34KSmZuacJyPFAUBeqC/98XXcCNXK/rz5L47rtddnJSNNv0lsIkzNptX0mwuSkV57fVY3/8Vx6gRy4WI8Zwx0i0kMSJLq8w3tO3RMR05NaaFpdeTUlPYdOqb6fMNZmygOAPJCfemfj+NGyFr9uen8Yd384W369MNPL8bm/cQmwrNcY+9frLGffvhp3fzhbdp0/jB1AplyNZ4zBrrFJAYkSbWhqo6ePrvqa0dPn1VtqOqoRRQHAPmhvvTPx3EjZK3+vOHyrbrtoRPEJoLWqcbe9tAJ3XD5VuoEMuVqPGcMdItJDEiS6nMN7RrfuOpru8Y3qj7n7qaJ4gAgL9SX/vk4boSs1Z9bLxwlNhG8bjV264Wj1AlkytV4zhjoFpMYkCTVBqvav3unLtsypoGK0WVbxrR/907VBh2uxKA4AMgJ9aV/Po4bIWv154tn68Qmgtetxr54tk6dQKZcjeeMgW4NuG4A3Gg2rerzDdWGqqrPNVQbrGpsZEgH9kys+lqlYpy1sVUc9h06pqOnz2rX+EaKA1BCnepVv7WJ+tK/SsV4N25kKY+4W0urP0eGq9q/e4f2HTpObCI3ecd35xq7QyPDA9owEE+dgHudYu3e3Tt03mBF07MLudXu2MdA3zGJ4ak8B5fWATjtN+9jI0MaHV4MidZnl5IWh6JvNAEUZ6161U+eh3Lz4WN9W9Wm+aU2GePFuJGVRqOpqfqcbmybSOg37tZTqRjVhhZ/ycsyNn2MI7iTV11dyacaW1T8k2fFWtnfI8NVHbhuQrXhqqbfXNCX/tv3tf8bJ3Ot3Vxvt9hO4qG8T9kN6UC7SmXxxrh1g9xpAoMnDADxyrNerVdfXPOxvvnYpqw1m1Yzcw3deOi4s3Eyy9gswzVDOkXdB/pQY4uKf/KsWO39/akvTeqN+Ybqsw391p9/W/c88Xyusc31do9JDA/lPbjEdKBdSBMyANKLqV6l5WN987FNWavPNzQyPBBN3JXhmiGdMtXVouKfPCtWt/6uDRcT21xv95jE8FDeg0tMB9qVaSAGyiimepWWj/XNxzZlrTZU1clXp6OJuzJcM6RTprpaVPyTZ8Xq1t/12WJim+vtHpMYOWg2raZnF9S0S59TLi3Ke3Dp5zTdfl9b1so0ECOZ8dsfSfUBN5LWkjKf/u1TfWtdr6JuEF2qzzX02Hde1uc+vn1V3N27e0fmcVfEmOpTHBXFt3sV3/hSV32L/37aU8Y8SyPra92tvysVFRLboVzvmGuhsTb8FzMxMWEnJyddN0NSNoclFXHgUi+H0RTRrrRyaFNhL8SnuI1J2omJ03ddlVNLVutlwiRh24KL2bR5W9bDs3ypuSvbcdEFw7rlI9t064Mn+m1TIS+gl5htvd5DT/5AH3n327T1wlHNzC5oZKiqajW7936Kur6+xFFRcny9wdXatbiuq77Ff7/t8TTPvIjZPPpmre8pKffY9vR6rxJCG7tI1DgmMTI2PbugvQcndeTU1PLXLtsypgN7JlKd3O56cOkkq9eWtW591WMfelHw0TsmMfKTVcz6Wkt81M9YkNU40n69rn7Pxbr5w5dq81itn+/r7SSGVMwYXGQe+HhPkVebcuzX4Gqtz7K+TmvFU5JYy6I9HuaZFzGbV0667m/XPz9Ju16Yquuex5/T4adekhTMvVaiTvT6FYQoqz1SrROdJT8edyr5u/+rU18FPPsIRM/XWuKjXseCLGtg+/U6/NRL+urTL+u5z/6iN+NT1ooYg4vMA9/uKfIco6kvYcjyOq0XT0niP4v2+JZnvsgrJ133t+uf30mnXPjcx7dLWhy7Y6qFnImRsVD2SPUipNfGqcGAv0KqJaHKsgZyvfJR5n7Nc4wuc7+GJMvrlEU8ETf5oW+L0ykXbnvohG64fKukuPqdSYyM+XJYUh5Cem28EwP4K6RaEqosayDXKx9l7tc8x+gy92tIsrxOWcQTcZMf+rY43XJh64Wj0fW7H2tfIlKpGI2NDOnAngnv9kj1K6TX1pr1Xbn/rjX76MuSL6CsQqolocqyBnK98lHmfs1zjC5zv4Yky+uURTwRN/mhb4vTLRfemGss9n9E/c5KjBy09khVzNLnSIJFCue1MesL+C2UWhKqrGsg1ysfZe3XvMfosvZraLK6TlnFE3GTH/q2GF1zYagaXb97+5a0MeZfSPqipHdLspJ+w1p7xG2rEApmfQGUGTUQPiM+kSXiCVhUplzwdhJD0r2Svmat/T+NMUOSaq4bhLD4eGowABSFGgifEZ/IEvEELCpLLnj5yowxF0h6v6RfkyRr7ZykOZdtAgAAAAAAbvl6JsYWSWck/Zkx5pgx5ovGmBHXjQIAAAAAAO74OokxIOmnJf2htXanpBlJt6/8B8aY640xk8aYyTNnzrhoI5AacYvQELMIDTGLEBG3CA0xC5d8ncT4oaQfWmufXPrzX2pxUmOZtfY+a+2EtXZi06ZNhTcQ6AVxi9AQswgNMYsQEbcIDTELl7ycxLDW/ndJLxpjti196UOSvuuwSQAAAAAAwDEvD/Zc8u8kfWXpySSnJP264/YAAAAAAACHvJ3EsNYelzThuh0AAAAAAMAP3k5iAJDGb3+kkJ9z+q6rUv37XtqV9mcAAAAAQDsvz8QAAAAAAABoxyQGAAAAAAAIApMYOWk2raZnF9S0S5+b1nWTAMA5aiNQPuS9G/Q7UDzyrhi5nolhjPl1a+2f5fkzfNRsWk3NzGnfoWM6evqsdo1v1P7dOzU2MqRKxbhuHgA4QW0Eyoe8d4N+B4pH3hUn75UY/ynn7++l+nxD+w4d05FTU1poWh05NaV9h46pPt9w3TQAcIbaCJQPee8G/Q4Uj7wrTt8rMYwxJ7r9laSL+v3+IaoNVXX09NlVXzt6+qxqQ1VHLQIA96iNQPmQ927Q70DxyLviZLES4yJJ10n6Pzp8TGXw/YNTn2to1/jGVV/bNb5R9Tlm4QCUF7UxXuwBdsf3vifv3Qix332PZaCTlXE7M7sQXN6FKotJjP8qadRa+4O2j9OSvpXB9w/OeQMV3XvtDl22ZUwDFaPLtozp3mt36LwBzlEFUF61war27965qjbu371TtUHeoQhZaw/w3oOTuvSOR7X34KSmZub4BaQAIfQ9ee9GaP0eQiwD7drj9s/+/vvn/A7oc96FrO/tJNbaT63xd/9Xv98/RG8sNPXAP7ygO69+l7ZeOKqTr07rgX94Qb/xr7dotMpEBoByqlSMxkaGdGDPhGpDVdXnGqoNVjnsKnAr9wBLWt4DfGDPhEaHcz0/vPRC6Hvy3o3Q+j2EWAbatcftPU88L0m677r3amR4wPu8CxlVIQe1oar2f+PkciBL0kDF6Lc/dEnHf99sWtXnG0EMMgDQj0rFLN+QcmMatpVj151Xv0tf+OZJHX7qJUnsAS6K7/uvV8aIJMmS90UKqd76Hstr4T6+vDrF7f5vnNRvf+gSVcyP848YyR7LAnKQZh8iy+cAAKFpH7vuPPyMbvmFbbr6PRdLYg9wUXw+94D7G6ThcyyvhTgvtyRxS4zkg0mMHKTZh8ijeAAAoek0dt320AndcPlW9gAXyOdzD7i/QRo+x/JaiPNySxK3xEg+/F5bFqg0+xBDXj4HACinbmPXJReNLo59LJUthM/nHnB/gzR8juW1EOflliRuiZF8sBIjJ619iK39UN2KcKjL51zh8VtA+ZD3/llr7FprzEP2kt5vFM3l/Q01I0yuYrmfeOE+HuvFbRljpIgazCSGY3kun4ttEGdPGVA+eeZ9bDWySKEu/UZxXMVI0ppB/vvHxTXpd4yhFmI9scZIt3wt6vc1tpM4ltfyuVYA7Tt0TEdPn9Wu8Y3av3unxkaGvHmXJi0evxW28dsfSf3/nL7rqhxagpDklfcx1sgihbr0G8VxFSNJagb57x9X16TfMYZaiPXEGCNr5WtRv6+xEsMDeSyfi/EQGfaUAeWTV97HWCOL5us2BvjDRYwkqRnkv39cXZMsxhhqIdYTW4ysla9F/b5W+kmMWJcTxvgLfxn3lAFltLIuz8wu5JL3MdZIoMxadaM+u/69Avm/yKd7YFfXhHtL5MmnHMvSWvlaVE6VehIj5jMWkgZQSMkV654yAD/WXpf/7O+/r3uv3ZF53nPjulpIY0Fs6Pv+rawbn/mrp3X3NdvXfuQh+e/dPbCra9J+b3nzFZfojz/5XmR/b6kAACAASURBVNWGquQjEnF9NoQLa+VrUb+vlfoggaz37DSbdnkZjev9Tq0Aat+rtDKAQtsTGuOeMgCrtdfle554XpJ033Xv1cjwQGZ5n6RGtvhU2/MQ2lgQE/o+G28uNDQzu6Av/+b7dPLVaT3x3Vf0+7/yU9o8Vuv8yMMU+R+rpPfARdU/V9dk5b3leYMVTc3M6bf+/NvkIxLx4WyIvKyV+2vla1G/r3nbg8aYqqRJSf9srf2lPH5GlkvXfLsRSRJAISZXa0+ZJG/bCKB3nery/m+c1G9/6JLlvaRZSDrI+lbb8xDiWBAL+r5/zebitrNPP/z0co5+7uPbdc/j39M9v7qjYz/ypkiye+Ai65/La9K6t5yeXdCNh46Tj0hsrRoe8ra19XJ/vXwt4vc1n7eT3Cjp2Tx/QJZL13w8JGq9Q2RCTi4AcSpySXGSg7Z8rO1ZYyxwh77v32KOHl+Vo7c9dEI3XXHpmnUjtoP20kpSa4uuf66vCfmItHw4GyIPSXLfdb56OYlhjHmHpKskfTHPn5Plnp0QC1/IyQUgTr6dfRNibU+LscAd+r5/3XJ081itVNtD0kpSa8tQ/1YiH5GWD2dD5CGE3Pd1bdTnJf2OpPPz/CFZLl1rBXFrOZH04yD2dQkae0IB+Ma3Zd4h1va0GAvcoe/71zVHZxsa3RBHjuYh0bbjEtS/lchHpOXD2RB5CCH3/WjFCsaYX5L0qrX228aYD6zx766XdL0kbd68ueefl9WenRALX8jJFaqs4hYoiouY9ensmxBre1qxjQUh1dnY+t6Frjnq0TuGSfhYa8tQ/1YiH9MJqdbmxYezIfIQQu4ba/16zIsx5vclfVLSgqQNki6Q9LC19hPd/p+JiQk7OTlZUAu7i/0E+3aRvt7CXkCSuB2//ZFC2nL6rqtS/Xtf2yWlb1svP6MXvfRZwrZ5FbPtYqgTMbwGDxXSgb7cHyBfveRoD/+P17U2L1nUP2qoM6WMWWQjq7zNq9Z6NyVkrf20pE9L0tJKjFvWmsDwSaizbb0ow4n9APoTS50oU20HQpQ2R2OpTUXot/7R10CYsrj3yTP/vTzYE/4rw4n9APpDnQDgI2pTcehroLzyzH+v31Ky1n5L0rccNwMdhHBqLQC3qBMAfERtKg59DZRXnvnPSgz0hMdQAVgPdQKAj6hNxaGvgfLKM/+ZxEBPQn72MYBiUCcA+IjaVBz6GiivPPPf6+0k8BePoYpLUU8bQblQJwD4iNpUHPoaKK8885+VGI40m1bTswtq2qXPTb8edZtE69Tailn6zIAEoE23OhFDDUR5EK/x4R6mOPR1MtSZ7NGn7uWV/6zEcIDHTQEoM2ogQkK8AsgbdSZ79GncWInhAI+bAlBm1ECEhHgFkDfqTPbo07gxieEAj5sCUGbUQISEeAWQN+pM9ujTuDGJ4YBPj5tirxiAovlUA8uAOt+fVrxe/Z6L9dhN79c//d5H9cTNP683eTcPQAe91FzGxewV0aeMr+4wieGAL4+bau0V23twUpfe8aj2HpzU1MwcCQggV77UwDKgzvevNljVH33ip/U7V27TnYef0bbPPKpPP/y0ZrhhBdCm15rLuJi9vPuU8dUtDvZ0wJfHTa3cKyZpea/YgT0TGh0mNADkw5caWAbU+f5VKkbVSkW3PniirR+P048AVum15jIuZi/vPmV8dYsedqT1uBlJzgKdvWIAXPGhBpYBdT4btWH6EcD6+qm5jIvZy7NPGV/dYjtJiXXdKzbL/jsA7rHXtH/ss85GXv1IjCMtYsZv1NzyyPNak+frYxKjxBb3iu1YtVfs7mu2q9FskiwAnGKvaTbYZ52NPPqRGEdaxIz/qLnlkde1Js+TYa1SgJpNq/p8o+/9XZWK0cjwgH7/V35K79xY08lXp/Wfv/Y9nXl9NvP9XFm1GUA5uNprGlutSrsnOLbXn5U89laHvp86y1gh7pIJPWZWivWad6sVkjQ9uxDd6y2zPMaFZtNqZm5BG0eGdOfV79IXvnlSh596ycs8d53D/vQEEmnNzu07dExHT5/VrvGN2r97p8ZGhnoKnA2DVV1xz99qYcXs3kDFZLqfK+s2A4ifi72msdaqpHuCY339Wcl6b3XI+6mzjBXiLrmQY2al2K95e62I/fWWWZbjQqc4+dzHt0uSvvr0y17luQ8xzXaSwKychV9o2uVZ+HqPz6svYu9e1m0GED8X+4rLXqvK/vqLFvLe+SxjhbhLLuSYWals17xsrxe96RQntz10QjdcvtW7PPchpks5iRHyYSlZz8IXsXcvlncOABTHxb7iPGpVSOMNtbpYIe+dXytW0sY6cZdcyDGzUuzXvL3ux/56kY1ucbL1wtGuee7qHsOHmC7ddhIflr/0ozUL39oPKf14Fr6XZUxFPJc66zYDiF8Rtald1rUqtPGGWl0sFzGelW6x8sJUXVfc87epYp24Sy7kmFkp5mveqe7/8SffG+3rRXa658VCx1rq8h7Dhxw21vr7rlBSExMTdnJyMtG/nZ5d0N6Dk6s6/bItY94dltJNaDfFUn5tzulAmcI6MUncjt/+SEGt8dPpu65K/f/E1GcJX79XMRuyrGtVaONN59e/QyPDA9owmPkvTIXEbdqYdX1QWSg6xcrd12zXf/7a93T4qZckJY/1gO5rqLUZ8f2a91MHOtX9m6+4RNe+b7NuPHS86NdLzHogaTylzQuX9xg553Cib+DfXVTOfFj+0o8QZ+HzOr3X5wEQQHiyrlWhjTfnvP7ZhhrNpj71pclS1FnGleQ6xcpn/urp5QkMKXmsh3hfg/74fM37rQOd6v7+b5zUDR/c6uXrRb7SxFPavHB5j+FDDnt5JoYx5p3GmG8aY541xjxjjLkxq+8dw6FIrZNwK2bpcwBFMOs2+3CgDID4ZFmrQhxvVr5+GenffvkfS1NnGVfSaY+VV340u+rv08R6iPc16I+v17zfOtCt7r8x3/Ty9SJfaeMpTV64vsdwncNeTmJIWpD0H6y1/6ukn5V0gzHmf8viG8dyKFLZhfYOJ4DyCX28KVudLdvrzVLosQ609FsHyAWslOe4UvZY83I7ibX2ZUkvL/3368aYZyW9XdJ3+/3ePix/Qf98OFAGANYS+nhTtjpbttebpdBjHWjptw6QC1gpz3Gl7LHm60qMZcaYcUk7JT2Z1fd0vfwF/Sv77COAMIQ83pStzpbt9WYt5FgHWrKoA+QCWvIeV8oca16/tWCMGZX0kKSbrLU/avu76yVdL0mbN29e8/vEdNp4TK+lH6HOPqaJW8AHxGw5dBpbJOm8waq+svd9qs82VKlIGwbirbNFjSuM492VuW/Sxm2Z+ypPedWBGK9X3vcHMfRZnuNKDP3TD29XYhhjBrU4gfEVa+3D7X9vrb3PWjthrZ3YtGlT1+/TOhV278FJXXrHo9p7cFJTM3NqNsN7tGxMryULIc4+Jo1bwBfEbPw6jS2vvzmvqZlZ7b1/6Wv3T2pmNowDLvuJ2bzHFcbx7sreN2nitux9lbes60Cs1yvP+4OY+iyPcSWm/umVl5MYxhgj6U8kPWutvaef7xXTaeMxvRYAgB86jS3/oz6vfYeOM95kjHG8O/omOfoqLFyv9OiztdE/nk5iSPo5SZ+U9EFjzPGlj4/28o1iOm086WtpNq2mZxfUtEufSzQrBwAuhVh/O40t79xYi2bs9EnI9yR5x3bIfVO0WPsqxPqZRKzXK0/02dry7J9Q8tDLSQxr7d9ba421dru1dsfSx1d7+V6un6GbpSSvheVFAOBGqPW309jy4tl6NGOnT0K9JykitkPtGxdi7KtQ62cSMV6vvNFna8urf0LKQy8nMbJU1GnjRcxaJXktLC8CADeKrr9ZjTudxpa31Aa1f/eO6J/UUfQ7TqE+AaWI2A61b1yIsa9WxthHf+ptuvPqd2njyJBm5vx9JzipGK9X3kLuM19+J+xFSL9Hev10kiwUcdp4a9Zq36FjOnr6rHaNb9T+3Ts1NjKU6c9J8lpYfgUAbhRZf7Mcd7qNLZKCewJUGkWN3SuF+mStImI71L5xIca+asXY1e+5WLf8wjbd9tCJwvIybzFer7yF2mc+/U7Yi5B+j4x+JYaU/2njRc5arfdaWH4FAG4UWX+zHnc6jS0hPgEqDVfvOIXYr0XFdoh940psfdWKsRsu36rbHjoRxDvBacR2vYoQYp/59DthL0L6PbIUkxh582nWKuTlVwAQsiLrr0/jTqjow+S4t0DeWjG29cJR8hLBCn1cCanWR7+dpAitWasjp6aWv9aatRodLraL81pe1Gxa1ecbQS3pAoCsJKmBRS5/9WncCVVWfViG8THUpd3wT7d8acXYzNwCtQ3BymJccTmmhFTrWYmRAd9mrbJeXhTSSbUAkLU0NbCo5a++jTshyqIPyzQ+hri0G35ZL18qFaORoQFqG4LV77jiw5gSSq1nSjMDIc1a9WLl/i5Jy/u7DuyZYFYcQPR8rIGxjztFyKIPfYwNwFdJ8oXahpD1G7+MKcnRGxlpzVpJii7IQt/fBQD98LUGxjzuFKXfPvQ1NgAfJc0XahtC1k/8MqYkx3YSrCukk2oBIGvUQHRDbADJkS/A2siR5JjEWEezaTU9u6CmXfoc4T7X9bD3GkCZFVkDGXPCUtbxkThFL8qaL1ki9+LVbFpVjLR/9w5yJAHWaK2hdbjKvkPHdPT0We0a36j9u3dqbGSoVHvz2J8IoMyKqoGMOeEp4/hInKJXZcyXLJF78Vp5bS+6YFi//ys/pc1jNdVnF59SwvU9Fysx1rDycJWFpl0+XKU+X74lPaGcVAsAeSiiBjLmhKls4yNxin6ULV+yRO7Fa+W1/avjL+kDf/At/ZsDT0pG5EgXTGKsgcNVAABFYcxBCIhTwA1yL15c2/SYxFgDh6sAAIrCmIMQEKeAG+RevLi26TGJsQYOIAIAFIUxByEgTgE3yL14cW3T42DPNXAAEQCgKIw5CAFxCrhB7sWLa5sekxjraB1AJGn5MwAAeWDMQQiIU8ANci9eXNt02E4CAAAAAACCwCQGAAAAAAAIApMYAAAAAAAgCExiAAAAAACAIDCJAQAAAAAAgmCsta7b0DdjzBlJP1j641slveawOT6hL1ZL0h+vWWuvLKIxbXFbdsRqd+v1jW8xy7WkD7yptcRsT+iP1Vr94brWcl0W0Q+LvKmzUq73tCFeb9rcn0RxG8UkxkrGmElr7YTrdviAvliN/vAX16a70PomtPbmoex9ENrrD629eaM/VvOlP3xph2v0w6Ky9EOIr5M2F4PtJAAAAAAAIAhMYgAAAAAAgCDEOIlxn+sGeIS+WI3+8BfXprvQ+ia09uah7H0Q2usPrb15oz9W86U/fGmHa/TDorL0Q4ivkzYXILozMQAAAAAAQJxiXIkBAAAAAAAixCQGAAAAAAAIApMYAAAAAAAgCExiAAAAAACAIDCJAQAAAAAAgsAkBgAAAAAACAKTGAAAAAAAIAhMYgAAAAAAgCAwiQEAAAAAAILAJAYAAAAAAAgCkxgAAAAAACAITGIAAAAAAIAgMIkBAAAAAACCwCQGAAAAAAAIQhSTGFdeeaWVxAcfWXwUhrjlI6OPwhCzfGT4UQhilo8MPwpD3PKR0UdhiFk+MvxIJIpJjNdee811E4DUiFuEhphFaIhZhIi4RWiIWRQtikkMAAAAAAAQPyYxAAAAAABAEJjEAAAAAAAAQWASAwAAAAAABMHpJIYx5k+NMa8aY76z4msbjTGPG2OeX/r8FpdtBAAAAAAAfnC9EuNLkq5s+9rtkr5urb1E0teX/hycZtNqenZBTbv0uZn4iTFAaZAnANAf6ihiQSwjRMStGwMuf7i19u+MMeNtX/6YpA8s/fdBSd+SdFthjcpAs2k1NTOnfYeO6ejps9o1vlH7d+/U2MiQKhXjunmAF8gTAOgPdRSxIJYRIuLWHdcrMTq5yFr7siQtfb7QcXtSq883tO/QMR05NaWFptWRU1Pad+iY6vMN100DvEGeAEB/qKOIBbGMEBG37jhdidEPY8z1kq6XpM2bNztuzWq1oaqOnj676mtHT59VbajqqEXJNJtW9fmGakNV1ecaqg1WmUXMmM9xWzSf8oTY746YRWhCjtm0tcinOor+hBy360kS18RyeGKO2aTOG6zozqvfpa0Xjurkq9P6wjdP6qtPv0zcFsDHlRivGGPeJklLn1/t9I+stfdZayestRObNm0qtIHrqc81tGt846qv7RrfqPpc51k5H/ZStZZD7T04qUvveFR7D05qamaOfV0Z8zlui9KKd0l64uaf19XvuXj579bKkzzbQ+x3R8wiNKHGbC+1KO39RtF8uL8JRahxu56kce17LK+lrHEea8wm1YrtOw8/o22feVR3Hn5Gt/zCNu374NZz4rasMZInHycxDkvas/TfeyT9tcO29KQ2WNX+3Tt12ZYxDVSMLtsypv27d6o2eO6snC+/QIW8HIrCEI72eP/0w0/rd67cpl/ecfGaeZLVz+4UJyHHPoB49FKLkt5vuBgnfbm/gVtJ4zrNvbNPVsb5zX9xXK+9PisZafpN7kdj9+ZCQ/XZhr78m+/TI/v+tTadP6zbHjqhX/u5n1gVt9TCfDjdTmKMOaTFQzzfaoz5oaTflXSXpP9ijPmUpBckXeOuhb2pVIzGRoZ0YM/EuktCVxZ3ScvF/cCeCY0OF3d5Ql3Gx4E6YekU77c+eEIHrpuQjHLbxrFWnIQa+wDi0kstSnK/4Wqc9OX+Bm4ljes0984+acX5pvOHdfOHt+m2h05wP1oCzabVzOyCPv3w08vX+3Mf3657Hv+eRjcMqGJ+fM2phflwuhLDWrvbWvs2a+2gtfYd1to/sdZOWWs/ZK29ZOnz2fW/k38qFaPR4cUgHh0e6FrAfPkFKtRlfLyLHpau8T5cXTNP+rVWnIQa+wDi0mstWu9+w9U46cv9DdxKE9dJ75190orzGy7fqtseOsH9aEks1tXjq673bQ+d0E1XXHpObFML8+HjdpJS8eUXqFCX8VEYwuIq3teKk1BjH0Bc8qpFrsZJX+5v4FbsY2wrzrdeOMr9aIl0q6ubx2rnxDa1MB+sYXGsVdzbl3kWXdyTLuPz7SkOrcLQWqIl/bgwsETLP0XG+8pYnZldWDNOQlzCCiAueS2ndzVOury/8e1epcxC2ibSS9y04vzFs3XuR0uka12dbWh0w+rrTS3Mh7E2/ENFJiYm7OTkpOtm9CyUAPPx/Ikc2lTYCwk9bntVRLy3x8W+D27VtT+z+f9n7+6DLLvK+97/1uk3zemBG7o9cHlvxkLKDVieMT0mE2LHMRCE5ZJdIa5L3wtMbGdk33LSYGJbwsot64+QiApFoamiYmuIzci4mlxblKOKkMHYUH6puapp0UIgE2AyNCBLtkbduYHug/rlnHX/6D6jfjmne59z9t7rWWt/P1VdLR0dda+91vM8a5/Ve6+td3/iUTOxmyNiFjEqJW6J2bBzd4jzmwKPl1qbsEHiptXyenazqdW1Tc3OmTrPIGYL0mu8JFYLi5apcSxiILOVtU2dvTC/a9Xx9PHJYBvTtAvCkZGaGutNjY8N51EYkiv4sSyS5alTrL73Ta/Wz/7DV+UVJ5YkF7OoBJOLGKnWy1SPq5MCz1WotQnrFjf3vut1Gh/Ntj+HwTwjZguUdbxDxYW1z209yNQ5ldgTg0dw5sPS/hM7H1d047/5I9123yNaWlm3MGEE0ynOq/pYp06xeu5PL2s8sg3DAJSnrHoZ4pwkxg0T+2XpXAXx6B43w5nrwEF5xmeR3lnvsyx1NeR5eOq1MPlFjKp+iCuCpY1peCrJbt3i/NnNavaTpVgFEIcy5hXOSYpH/Uc/usXN5adXBq4D5H3vUumzkJ9XUq+FyS9ipPBh18pKpKUdplNfXexVtzhvtVTJfrIUqztZyWUA++U9r3TK9xTOSayzWv+tYB7qrFPcfOBtN+kjn7s88HkTed+7LH0WQyyH/LySei00fUNMHmL/sGtpU5ZBdpjO+34wnkqyW9c4Hxvq2E/PbjTV8rJ032auLO6GbimXAeyX57zSNd+PjkZ9TrKTwfv/Jdms/1ZYmoesxU87bu591+tUHx3W5adX9MHPfFUPfPFJnT4+OdD5ZeyfRUI4rM8sxfJBQn5eKboWhs7h9K/EiPxSGmurt/3cV1vEJWGpry72qmucrzX39dNvvuOHtLq92U/Ml+gdxto94NZyGcBuec4r3fK9/bjnnWI6J2mzfqm3tfpvhZV5yGr81GpO46PDWl5d110PPK5PfempXM4vY/8sEsJhfWYllg8T+vNKUbXQQg4n/3SSWFbquml5rxvufEib20Fx6w++RL/0j6/Xq190NJdVrzJW0YraHbegtke5k3OnOL9n5oQm66Nyzu3qJ3np7H3F7VYcemXWqr25LEnDNaevvf+tqjke+4fKSfrpJN3y/av/9mYtr27sqtW/+Y4f0lCtpvpYPDUzsnk9L6ZqbT99VeA81BPLT01otfxWf44NqbHWVK0mXTc8+Ll2oM8ipmK2F4f1mZVYbrf1oFwsqq6FrJcF53Cmg0j+uvvYLyvceRnSrT/4Ev3KP7lRt9//WC5FsKyiWtRldO3VRUnBJ73QajWnifqIfuudr9P42NZlkJ94+Fuaef0rNTk+uqufWt4Xdllj7IuGReIWKMC+vOaVbvn+vY3WrnOSZzeaWl3b1OzHvxBVzSxiXmf+yK7fvrIyD1m9vaJbv143PPj5asyfRUI4rM+sxHKWXCzi80roemkhh5O/nUSK+7LCnZch/dI/vl633/9YbpdOlXUpFpfRleN7my39wu8+ou//9U/pLR/+M33os1/vOJ5Fjkcsl/eFEPqSQgDlOSjfd56TtLw0O/dodDWziHmE+SO7fvvKyjxk9bywyBiM+bNIKAf1mZlYDlS3QtdLCznMn/+M27sSmeeqV1mraO1Cs3e1kA9v+co6nkWOh4WVWav4SwxQHVnzPdaaWcQ8EmtfhNBvX1mZh6yeFxKD8TATy4FiJnSsWshhFjEi0F6JXNneECyvS6fKuhTLSqFJXdbxLHI8rFzeZxW3QAHVkSXfY62ZRcwjsfZFCIP0lYV5yOp5ITEYFwuxHCpmQseqhRyuxO0kqcj70qkyL8XiMrri9TKeRY2Hlcv7ACAGMdfMvOeRmPuibCn0lcXzwhT6FeUKFTMWYjV0Dif/dJLU5L0TrfGdwEOIdidnycZ4WmhDxUQds6gsk08nCYGa+RzjfWGq1hrvq2gl1q+mYjZVoWImsVjdiaeTpCjvS6csXIqF/FgYTwttAIBYUDOfQ19kR18Vg35Fr0LFTNVjldtJAAAAAABAFMwuYjjnftk597hz7svOuTnn3HWh2wQAAAAAAMIxuYjhnHuppFlJ097710oakvT2sK1KU6vltbK2qZbf/t6Kf48U9I94AIDOqI8AsqBWVAdjHY7lG2iGJR1xzm1Iqkt6MnB7ktNqeS2tru97xu/k+GgqG8OgB8QDAHRGfQSQBbWiOhjrsExeieG9/2tJH5T0LUlPSfqf3vvPhG1VehobTc3OLejilSVttrwuXlnS7NyCGhvN0E3LBaujvUkpHhh7AHlKqT5aQZ1GnqzEE7WiOqyOtZVcKJrJRQzn3Ask/ZSkV0l6iaRx59w79rznNufcvHNu/urVqyGaGb366JAuLS7veu3S4rLqo/E/D7u9Onr2wrxuuPMhnb0wr6XV9eCJbDluU4kHq2MfK8sxC3RSRMymUh+toE7vR63tn6V4qlKtqHrMWhxrS7lQNJOLGJLeJOkb3vur3vsNSZ+U9A92vsF7f6/3ftp7P33s2LEgjYxdY72pU1MTu147NTWhxnr8q8VWV0ctx20q8WB17GNlOWaBToqI2VTqoxXU6f2otf2zFE9VqhVVj1mLY20pF4pmdRHjW5L+vnOu7pxzkt4o6SuB25Sc+siQzs2c1OnjkxquOZ0+PqlzMydVH4l/tdji6qh1qcQDYw8gb6nURyuo08iTpXiiVlSHxbG2lAtFM7mxp/f+YefcH0j6gqRNSQuS7g3bqvTUak6T46M6f2Za9dEhNdabqo8MJbEZTXt19OKVpWuvtVdHj46ZDPvgUokHxh7Ix9QdD/b8/yzefUsBLQkvlfpoBXUaebIUT9SK6rA41pZyoWhWr8SQ9/43vPd/13v/Wu/9O733a6HblKJazeno2LBqbvt7IkXW4upoDFKIB8YeQBFSqI9WUKeRJ2vxRK2oDmtjbS0XipTWkkzEWi2vxkbTzEpeaIP2h8XVUZTDytjvjOFnN5pqtaT6GLEIAJ3q9JHhmhobTR0Zqamx3tT42DD1skd5nEvGeD5qZd4HBhXy809suW/2SowqSX0n2V4f9ZNXf1hbHUV5Qo59q+W18uym5KRnvrum3724qOXVdZ29L838BgCp97l+Z52ujwxpubGh3/7zK/rr//GsbrvvEeplj/I4d7J8PnpYfHHOh9jtzL/3/udH9cx31yQnrTzb22NS+8kFy7nfDYsYORnkmbwp7yTbT1Kk3B95qcozoGNzLd63Fyze98kv6ebXvliffOQJ4hkwiFqaj0FPgNvz/lte+2Ldfv9j1Ms+5HHuZOX8a29eNput6D5gobr6nVfa+XfseWN675tv1Ps++aWteL+v+Hi3kvu9YBEjB4NO3invJNtPUqTcH3mIcbW0KjrF+3s+8aje8toX73of8QyERy3Nz6AnwO15//oXHmX+71Me504Wzr865eXqenwfsFBNg8wr7fz7pX98femLuRZyv1csYuRg0Mnb4nOG89JPUqTcH3mIcbW0KrrF+/UvPLrrNeIZCI9amp9BT4Db8/7lp1eY//uUx7mThfOvTnk5PjYc3QcsVNMg80o7/0Is5lrI/V6xiJGDQSfvlHeS7ScpUu6PPMS4WloV3eJ9ZW2TeAaMoZbmZ9AT4Pa8/+kvP6UPOlp1wAAAIABJREFUvO0m6mUf8jh3snD+1SkvWdxCLAaZV9r59+3lRunxbiH3e8XTSXIw6DN5U95V+chwTffMnNC75x7VpcVlnZqaODQpUu6PPFTpGdCxaU8Cs3MLO+L9hMaGnM6/azrz00li2yEaiNEgtZQc3a1z7ct+Atye93/uR47ryEhN977rdTydpEd5nDtZOP/qlJef/vJTHc4lT5j+gIX9qlA3B5lX2vk3PjakczMnNNvDZ6dBWcj9Xjnv47/3c3p62s/Pzwf7/e37n/ZO3pPjo6YHv2jtfpl7+Jt6y2tfrOtfeFSra5saHx3S0JDZi4BKG7B+45Z4s23QSbqP8TUfs4jT1B0P9vz/LN59S9a3lhK3B8Vsv7WUGtxZBT6gUGtL0Dm/TujIyJCeWVnXyyfq+vZyQy+oj+h5142kFmN5MxOzVambeR1nBerpQTIdKIsYOal4sHW0srapsxfmd61Gnj4+qfNnpi1fMWCm4B+EeEtXH3kTRcwiPqkvYkj91dJI5zYMjlpbkr15WXPSz3+MnOuDmZitUt3kHH1gmTrL7J/DY5P386lTeOwb9xsXh+eh9y6WnCJvgPJ0q6UH1QtyFCjW3ry8bmSwnItl/k9ZEXXT6rhyjl4OFjEMSuWxbzHudIs0xZRT5A0Q1mH1ghwFyjVIzsU0/6cs77rJuIJFDINSeexbjDvdIk0x5RR5A4R1WL0gR4FyDZJzMc3/Kcu7bjKuSOsmpESkcqlqjDvdIk0x5RR5A4R1WL0gR4FyDZJzMc3/Kcu7bjKu4EqMQ4S43yqlS1W5L6w/Vu/zi1VsOUXeAOFkqRdVz1HmKJSt35yLbf4/TMy5l2fdTG1cpbjHNgSuxDhAqMcBDfq8dcStKo+hKhM5hdQU/OSQSqNeHIw5CjFJKZ/JveekNK4SY9sPFjEOsPN+K0nX7rcq+nFAXKpabaHiLmXkFICsqBcHY45CTFLKZ3LvOSmNq8TY9oNeOUDI+63al1xJIngrhvv8ikFOAciKetEdcxRik0o+k3u7pTKuEmPbD/bEOECK91vBPuIOAGAVcxQQBrmXLsa2d2YXMZxzf8c59wfOuf/mnPuKc+502W3gMWoIgbgDAFjFHAWEQe6li7HtneVrb+6R9Efe+3/mnBuVVC+7Aandb4U4EHcAAKuYo4AwyL10Mba9M7mI4Zx7vqQflfTPJcl7vy5pPURbUrrfCvEg7gAAVjFHAWGQe+libHtj9XaS45KuSvod59yCc+6jzrnxnW9wzt3mnJt3zs1fvXo1TCuBHhG3iA0xi9gQs4gRcYvYELMIyeoixrCkH5L0H733JyWtSrpj5xu89/d676e999PHjh0L0UagZ8QtYkPMIjbELGJE3CI2xCxCsrqI8YSkJ7z3D2//+x9oa1EDAAAAAABUlMlFDO/930j6tnPuxu2X3ijprwI2CQAAAAAABGZ515B/Jen3tp9MckXSzwZuDwAAAAAACMjsIob3/lFJ00X87FbLq7HR5BE2qBTiHgBQFOYYYAu5gLJUOdbMLmIUpdXyWlpd1+zcgi4tLuvU1ITOzZzU5PhoZQYd1UPcAwCKwhwDbCEXUJaqx5rJPTGK1NhoanZuQRevLGmz5XXxypJm5xbU2GiGbhpQGOIeAFAU5hhgC7mAslQ91iq3iFEfHdKlxeVdr11aXFZ9dChQi4DiEfcAgKIwxwBbyAWUpeqxVrlFjMZ6U6emJna9dmpqQo31dFatWi2vlbVNtfz295YP3SQUKMt4VyHuAQDFOWiuYY5BHlI4fyUXUJaiYi2WPKzcnhj1kSGdmzm57/6h+kgaq1ZVvz+qarKOd+pxD1um7niw8N+xePcthf8OAFsOm2uYYzCoVM5fyQWUpYhYiykPK7eIUas5TY6P6vyZ6SR3ct15f5Ska/dHnT8zraNjlRvu5GUd79TjHgBQnMPmGuYYDCqV81dyAWUpItZiykNbrSlJreauDYS1ARlU1e+PqppexjvluAcAFCfLXMMcg0GkdP5KLqAsecdaTHk48J4Yzrm/65x7o3Pu6J7Xbx70Z6N33ItXLYw3AKBozDUoGjEGhBdTHg60iOGcm5X0XyT9K0lfds791I7//O8G+dnoT/v+qNPHJzVcczp9fJJ78RLGeAMAisZcg6IRY0B4MeXhoNednJX0Ou/9inNuStIfOOemvPf3SOLmrwC4F69aGG8AQNGYa1A0YgwIL6Y8HHQRY8h7vyJJ3vtF59yPaWsh45ViESMY7sWrFsYbAFA05hoUjRgDwoslDwfdE+NvnHMn2v+yvaDxk5K+T9IPDPizAQAAAAAArhl0EeNdkv5m5wve+03v/bsk/eiAPxsAAAAAAOCagRYxvPdPeO//pst/+8tBfjZsabW8VtY21fLb31s+dJMqhzEAAHuozUB25AtwMHIkG7s3ukSo1fJqbDTNb4TSq1bLa2l1XbNzC7q0uKxTUxM6N3NSk+OjSRxfDGIZg1RzAAA6iaU2p465pzh59i35AhzMUo5Yr6uD3k6Cbe2gO3thXjfc+ZDOXpjX0up6bqtnIVflGhtNzc4t6OKVJW22vC5eWdLs3IIaG/aeGZyqGMag6ByIGavqQJpiqM0hlVH7mHuKk3ffNjaamnv4m7rr1tfoq//2rbrr1tdo7uFvki8wI/T5mpU5JYa6yiJGTooMutCBVB8d0qXF5V2vXVpcVn3U3jODUxXDGFgpvNaEzl8AxYmhNodSVu1j7ilO3n17ZKSmnz75Mt31wOO68d88pLseeFw/ffJlOjLCxxGEZ+F8zcqcEkNdpWrkpMigCx1IjfWmTk1N7Hrt1NSEGut2Ajl1MYyBlcJrTej8BVCcGGpzKGXVPuae4uTdt431pm6//7FdMXH7/Y+RLzDBwvmalTklhrpqdhHDOTfknFtwzv3X0G3JosigCx1I9ZEhnZs5qdPHJzVcczp9fFLnZk6qPmInkFMXwxhYKbzWhM5fAMWJoTaHUlbtY+4pTt59Oz423DEmxsfYog/hWThfszKnxFBXLVeNd0v6iqTnh25IFu2g27sRSx5B1w6ki1eWrr3WDqSjJRT+Ws1pcnxU589Mm93cJXUxjEGRORCz0PkLoDgx1OZQyqp9zD3FybtvmQ9hmYX4tDKnxFBXTVYM59zLJN0i6f2S3hu4OZkUGXQWAqlWc9cSmIkmDOtjYKXwWmMhfwFJmrrjwdBNSJL12hxKWbWPuac4efct8yEssxKfFuaUGOqq1dn2w5J+TdLzur3BOXebpNsk6RWveEVJzTpYUUG3N5Ce3Wiq1ZLkpJW1TXNBhe6sxG1Rj02yUHitiWEiOIiVmAWyImZt6KX2DTonpTD3WI3bPPs29vlwENYfV9kPqzHbLwvxaSlOrNdVc3tiOOd+UtLT3vtHDnqf9/5e7/2093762LFjJbUunGuB5KXVtabO3seTDmJkIW4t7L5cNe38rbnt7xGduFiIWaAXxKwdWWofc9KWqsRtzPNhv1KN8RRjNmR8phonRTG3iCHpDZJudc4tSvqEpB93zn08bJPssLBzLuJGDAEArGBOQuqIcWRBnPTG3CKG9/593vuXee+nJL1d0p96798RuFlmWNg5F3EjhgAAVjAnIXXEOLIgTnpjbhEDB+vlkTetltfK2qZafvt7hJcjpXAM1pT92CTrY2i9fQCqp0p1KdSj/KrUx6H02sepjkkMj6uMXQqxE1uchO5z04sY3vvPe+9/MnQ7LMn6/OAU7qtK4RgsKvMZ1NbH0Hr7AFRP1epSmXNSW9X6OIRe+zjlMQkR41WSSuzEFCcW+tx5H9cAdzI9Pe3n5+dDN6M0WXauXVnb1NkL87uedXz6+KTOn5k2ucNsJ4GOobQdfELGbVm7H1uPQ+vty8hczJbxKM/Fu28p/HdYZvVxqT2MSylxG+P5QSJ1qSdl78jfZx+bq7WW9drHqcd9oKdOVCJmU4odS08nOUjBfZ7pgOMaWUjK9sibFO6rSuEYrCrrsUnWx9B6+wBUTxXrUtmP8qtiH5et1z5OfUysP64yZinFTixxYqHPTd9Ogv7Fdl9VJykcQ9VZH0Pr7QNQPdSl4tHHxeu1jxkT9IvYKZ+FPmcRI1Ex3VfVTQrHUHXWx9B6+wBUD3WpePRx8XrtY8YE/SJ2ymehz+1ep4KB1GpOk+OjOn9m2vx9Vd2kcAxVZ30MrbcPQPVQl4pHHxev1z5mTNAvYqd8FvqcRYyExXJf1UFSOIaqsz6G1tsHoHqoS8Wjj4vXax8zJugXsVO+0H3O7SQAAAAAACAKLGIgaa2W18raplp++3tkz4xG+ohRAFlRLzAoYgg4HHliH9fbIFmtltfS6rpm5xZ0aXFZp6YmdG7mpCbHR7lPDiYQowCyol5gUMQQcDjyJA4sYiBZjY2mZucWdPHKkiTp4pUlzc4t6PyZae6XgwnEaLmm7niw8N+xePctPf8/ZbQL8aNeYFDEEHA48iQO3E6CZNVHh3RpcXnXa5cWl1Uf5ZFLsIEYBZAV9QKDIoaAw5EncWARA8lqrDd1ampi12unpibUWG8GahGwGzEKICvqBQZFDAGHI0/iwCIGklUfGdK5mZM6fXxSwzWn08cndW7mpOojrKTCBmIUQFbUCwyKGAIOR57EgRt7kKxazWlyfFTnz0yrPjqkxnpT9ZEhNuWBGcQogKyoFxgUMQQcjjyJA4sYSFqt5q5twsNmPLCIGAWQFfUCgyKGgMORJ/ZxOwkAAAAAAIgCixgAAAAAACAKJhcxnHMvd859zjn3Fefc4865d4duUwpaLa+VtU21/Pb3lg/dJAAiN4GqIvcB7FSFmlCFY0TxrN7ksynpX3vvv+Cce56kR5xzf+y9/6vQDYtVq+W1tLqu2bkFXVpc1qmpCZ2bOanJ8VE2qgECIjeBaiL3AexUhZpQhWNEOUxeieG9f8p7/4Xtf/6upK9IemnYVsWtsdHU7NyCLl5Z0mbL6+KVJc3OLaixwTOPgZDITaCayH0AO1WhJlThGFEOk4sYOznnpiSdlPRw2JbErT46pEuLy7teu7S4rPoozzwGQiI3gWoi9wHsVIWaUIVjRDlML2I4545Kul/Se7z339nz325zzs075+avXr0apoERaaw3dWpq4tq/3/qDL9Fn3/uPJCmq+9Fiv4+uinFracwstaVtb25K0qmpCTXWbfxVoooxi7jlFbNF1wvruR8zi7X+MGXX2hj7qChW+iK2mtBPzJZxjFbGs8rKGAOzixjOuRFtLWD8nvf+k3v/u/f+Xu/9tPd++tixY+U3MDL1kSGdmzmp08cn9dMnXqJfu/lGve+TX9INdz6ksxfmtbS6bj7J2/fRnb0wH1W7d6pa3FoaM0tt2Wlnbg7XnE4fn9S5mZOqj9j4q0TVYhbxyyNmy6gX1nM/VlZr/WHKrLWx9lERLPVFbDWhn5gt+hgtjWdVlTUGznt7g+qcc5IuSFr23r/nsPdPT0/7+fn54hsWuVbLb91z5qWz983r4pWla//t9PFJnX/XtOS2CozFzXVW1jZ19kKHdp+Z1tGx3PaoLe3ALcRtOybqo0NqrDdzH/uSxiy6tuw14DiYi9mpOx4svC2Ld9/S8/9T5XaVpYfjLyVu+62zZdWLZrOlxkZT42PDWl3bVH1kSENDZv++FIUCx85Erc1j3rY8H5bNWl/kfF5mImb3KvLc09p49qvo8/Mi5TAGmQ7U6kz5BknvlPTjzrlHt79+InSjYlerOR0dG1Z9rPP9aEdGh0yvWHIfXb5K+UujoTGz1Ja92rlZc9vfI5mogFSVUS9aLa/lxoZuu+8R3XDnQ7rtvke03NgwOf/GxHKtH1Re83bKfdQra31RhfOBIo/R2nj2I/arScoaA5NLUt77v1CJq4dV074fbecK2ampCV1+euXaLsEWVyy7tbux3jTX1hjs3CFaUiFjb2nMLLUFg7N69YLVdqE3ZdSLMmpwFaVc6/OKmZT7qFf0RVpSGM/Y54ayxsDqlRilqeLmL53uR/vA227SRz53WZLdFcvY7hW0rqiV0p05VXPSuZkTJsaM+AGQVRn1IoW/GFrSnnuOjNR0j5F5J295xUyn+L5n5oSODFfvYwHnBmmxNp79fM6MfW4oawzsL+cUqH25zuzcgi4tLuvU1ITOzZzURH1E39tsRXkfUha1mtPk+KjOn5lWfXRI31pq6IOf+aoe+OKTkuyuWO5td4pjU6YiVko75dRvvuOHdP5d06qPhR0zi/ET8z2PQMoOqxd55G4KfzG0Yu/cM/vj1+u33vk6Hb1uOKnamlfM1GpOE/UR/dY7X6fxsWFdfnpFn3j4W5p5/Ss1OT6aqa9Smb8snhtgSz8xZmk8u33OPCzHYp8byhqD6i257rDzcp3NltfFK0uae/ibWmrEex9SVu370eSl8bFhXf3umokVy8NU4V7BshSxUtopp37x41+QnEyMmaX4if2eRyB13epFbvsSGPuLYcz2zj0f+uzX9Qu/+8i1k/5UzhXyjJnvbbb0C7/7iL7/1z+lt3z4z/Shz35ds3MLWxvAHyK1+cvSuQG2DBJjVsaz0zlxlhxLYW4oYwzsL+cUqNPlOm957Yv17rlHo70PqVeWVixRriLGPvZL4MoU+z2PQFXllbvMv/mpytyTZ8wM0mfMXyhaCjHWb44xN2RT7Ssxti/X2en6Fx6txES4k5UVS5Qv77HvlFPtS+CwW1VOuoHU5Jm7zL/5qNLck1fMDNJnzF8oWgoxNkiOMTccrtKLGJ0u11ld26zMRAjkLYVL4MpSpZNuICXkrj3MPb0bpM/IARQthRijLhUrjutxCtLpcp0jwzWdmzm5bxMWAg44HJfAZdee3Kg1QFzIXXuYe3o3SJ+RAyhaCjFGXSpWpRcxpB0bXErXvg8acFl2001lV2ekq98Y7ZRTIVjPMSY3IB676slGUxP1kVxy13qdiomVuScm/fZZXvMX8b9byv3R67GlEmPUpeLQmx0MEnBZHqfT7yN3gLLEHqOxtJ/JDbDvwHriXN+5G0udAjoZdP4i/ndLuT/6PTZiDAep9J4YRWjvpnvseWN6cPZH9PF/8Xqtrm3q2c3mvvf0+sgdoCyhYrTV8lpZ21TLb3/v83Ft5BiAvBRVT6pUp/Kq7eiN5X6vUvxnkXJ/hDq22M9lcTD+9Jez+uiQXvT8Mb33zTfq9vsf27Hyd0LXDW9dwpTCjrtIW4gYzXPFnBwDkJei6klV6hR/DQ3Der9XJf6zSrk/Qh1b7OeyOBhXYuSssd7Ue950g26//7E9K3+PXlv5S2HHXaQtRIzmuWJOjgHIS1H1pCp1KuW/MFtmvd+rEv9ZpdwfoY4t9nNZHIxFjJzVR4b0isn6gSt/PHIH1oWI0TxXzMkxAHkpqp5UpU6l/Bdmy6z3e1XiP6uU+yPUscV+LouDcTtJzmo1p5VnN3VqakIXryxde7298nd0bDiZpxKE3vEXxckSo3mPf3vFvFve5N1+AMiiqHpSlTqVZ23PU+rnMJb6vVtfVyH+s0q5P0IdW4jfaynvrCiq1nIlRgHqo4ev/LV33G3vbB5bkWrf83X2wrxuuPMhnb0wr6XVdTavSchBMVrE+Oe9Yh57jgGwo6h6UoU6ZfEvzFU4h7HS7wf1dRXivxcp90eoYyv791rJOyuKrLXO+/gL9vT0tJ+fnw/djF1SX+FfWdvU2Qvzu1YaTx+f1Pkz07GvNJY2SBbjNquixj/1vCmIuZiduuPBEloDixbvviXrW0uJ25jrbEqs1fY+5zBztfYwFvo94fPFGEQXsymwkHdWFFlrqR4FGfTZxtZxz1e1FTX+qecNAFSRtdpelXMYC/1elb4G2izknRVF5j+3k6AvKe+ijMMx/gCAWDGHlYe+BqqryPw3u4jhnLvZOfdV59xl59wdoduD3bjnq9oYfwBArJjDykNfA9VVZP6bvMbFOTck6SOS3izpCUmXnHMPeO//KmzL4pbnPVop76KMwzH++eL+SQApsV7TmMPKY6Gvrccj7COG+lNk/ptcxJD0w5Iue++vSJJz7hOSfkoSixh9au8OOzu3oEuLyzo1NaFzMyc1OT460EIG93xVF+OfjyJyEwBCiaWmMYeVJ2RfxxKPsIsYGkxR+W/1dpKXSvr2jn9/Yvs19Kmx0dTs3IIuXlnSZsvr4pUlzc4tqLHBPYlASOQmgJRQ02AJ8YhBEUM2WV3E6LSstetZsM6525xz8865+atXr5bUrHixO7QNxC32sp6bxCxiQ8yGZb2mWUXcFoN4LE5VYpYYssnqIsYTkl6+499fJunJnW/w3t/rvZ/23k8fO3as1MbFiN2hbSBusZf13CRmERtiNizrNc0q4rYYxGNxqhKzxJBNVhcxLkl6tXPuVc65UUlvl/RA4DZFjd2hAZvITQApoabBEuIRgyKGbDK5k5H3ftM59y8lfVrSkKTf9t4/HrhZUbOwOzSA/chNACmhpsES4hGDIoZsMrmIIUne+09J+lTodqSEnbgBm8hNACmhpsES4hGDIobssXo7CQAAAAAAwC4sYgAAAAAAgCiwiAEAAAAAAKLAIgYAAAAAAIgCixgAAAAAACAKznsfug0Dc85dlfTN7X/9PknPBGyOJfTFbln64xnv/c1lNGZP3FYdsdrdYX1jLWYZS/rATK0lZvtCf+zW7o/QtZZx2UI/bDFTZ6VCz2ljHG/aPJhMcZvEIsZOzrl57/106HZYQF/sRn/Yxdh0F1vfxNbeIlS9D2I7/tjaWzT6Yzcr/WGlHaHRD1uq0g8xHidtLge3kwAAAAAAgCiwiAEAAAAAAKKQ4iLGvaEbYAh9sRv9YRdj011sfRNbe4tQ9T6I7fhja2/R6I/drPSHlXaERj9sqUo/xHictLkEye2JAQAAAAAA0pTilRgAAAAAACBBLGIAAAAAAIAosIgBAAAAAACiwCIGAAAAAACIAosYAAAAAAAgCixiAAAAAACAKLCIAQAAAAAAosAiBgAAAAAAiAKLGAAAAAAAIAosYgAAAAAAgCiwiAEAAAAAAKLAIgYAAAAAAIhC0EUM59xvO+eeds59ecdrE865P3bOfX37+wtCthEAAAAAANgQ+kqMj0m6ec9rd0j6E+/9qyX9yfa/AwAAAACAinPe+7ANcG5K0n/13r92+9+/KunHvPdPOedeLOnz3vsbAzYRAAAAAAAYEPpKjE5e5L1/SpK2v7/wsP/h5ptv9pL44iuPr9IQt3zl9FUaYpavHL9KQczyleNXaYhbvnL6Kg0xy1eOX5kMZ32jNc652yTdJkmveMUrArcGyIa4RWyIWcSGmEWMiFvEhphFSBavxPjb7dtItP396U5v8t7f672f9t5PHzt2rNQGAv0ibhEbYhaxIWYRI+IWsSFmEZLFRYwHJJ3Z/uczkv5LwLYAAAAAAAAjQj9idU7SRUk3OueecM79vKS7Jb3ZOfd1SW/e/ncAAAAAAFBxQffE8N7PdPlPbyy1IQAAAAAAwDyLt5MgEq2W18raplp++3sr84aySADjjyyIEwCoNuYBoLqKyv9on06Cw7VaXo2NpuqjQ2qsN1UfGVKt5nL72Uur65qdW9ClxWWdmprQuZmTmhwfze13wK5exr/IOIRt1usEsQkAxeJ8AUhTlnwt8jyQKzES1Q6asxfmdcOdD+nshXktra7ntvrV2Ghqdm5BF68sabPldfHKkmbnFtTYaOby82Fb1vEvOg5hm+U6QWwCQPE4XwDSkzVfizwPZBEjUUV/eKiPDunS4vKu1y4tLqs+OpTLz4dtWcff8odYFM9ynSA2AaB4nC8A6cmar0WeB7KIkaiiPzw01ps6NTWx67VTUxNqrDPZVEHW8bf8IRbFs1wniE0AKB7nC0B6Mi9OFngeyCJGoor+8FAfGdK5mZM6fXxSwzWn08cndW7mpOojTDZVkHX8LX+IRfEs1wliEwCKx/kCkJ7Mi5MFngc67+O/12x6etrPz8+HboYpZWyol+gGTKUdQOxxG3pDH1xjOmat1gliM7hSOjn2OgtTTNdayzhfCIaYRSEK3rA3U9zydJJE1WpOk+OjOn9murAPD7Wa09GxrRBqf0d1ZBn/MuIQtlmtE8QmAJSD8wUgLb3ka1HngXbOKJE7qx8eUC3EIawiNgHADmoyEI/Q+cqeGAAAAAAAIAosYqAnrZbXytqmWn77e8nP7w79+9G7UGNGrKSDsQyPMQCQqnZ9a7Za+u6zG9Q5JCPlc3Cu1UJmoTddCv370btQY0aspIOxDI8xAJCqdn2be/ib+umTL9Pt9z9GnUMSUj8H50oMZNbYaGp2bkEXryxps+V18cqSZucW1Ngo5/FXoX8/ehdqzIiVdDCW4TEGAFLVrm9vee2Ldfv9j1HnkIzUz8FZxEBm9dEhXVpc3vXapcVl1UcHf9ZvDL8fvQs1ZsRKOhjL8BgDAKlq17frX3iUOoekpH4OXvlFjDzv2Un9nuHGelOnpiZ2vXZqakKN9ZKuxAj8+3G4Vstr5dntHHh2U6trm0HGjFiJ285aGiqGurUnxdp+GPIJSFOW2pZ6/WvXt8tPr1DnkLuQ+TPo3N1v28s6Z6j0Ikb7np2zF+Z1w50P6eyFeS2trvcVYHn+LKvqI0M6N3NSp49ParjmdPr4pM7NnFR9pKQrMQL/fhxsKwfWdPa+7Ry4b15rm03dM3Oi9DEjVuK1t5b+zl98Q/e8vfwY6taeFGv7YcgnID1ZalsV6l+7vn36y0/pA2+7iTqH3ITOn0Hm7kHaXtY5g/M+/kI0PT3t5+fne/7/VtY2dfbCvC5eWbr22unjkzp/Zrrn593m+bMsa7W8GhtN1UeH1Fhvqj4yVOqGRyX8/tIOpt+4tapbDnz47SdUHx3S+NhwqTETOlZLlFTMdoqj977p1frZf/iq0mOoW3tSrO2HKSCfShnA1Oosgkq+1u6tbVWpf+36dmSkpsZ6M8hcU5CkYjY2FvKn37l70LYPeM6Q6Y2VvhIjz3t2qnLPcK3mdHR/n0L3AAAgAElEQVRsWDW3/b3k4h7696O7bjnwfUfHNB5gzIiVOHWKo3N/ejlIDHVrT4q1/TDkE5CWLLWtKvWvXd+GajU977oR6hxyYSF/+p27B217GecMlV7EyPOeHe4ZRtV1y4FvLzfIA2RmrZZaaw8A5CFLbaP+Af2LOX9iaHulFzHyvGeHe4ZRdVs5sHvvgv/wMzfpBfUR8gCZWaul1toDAHnIUtuof0D/Ys6fGNpudk8M59wvS/oXkrykL0n6We/9s53eO8h9WHne51uhe/BTxv2DA2i1/Fbsjw2psdZUrSZdN0weFCy5mLVWS621JxHsiYHYVLLWUv+illzMxibm/AnY9nj3xHDOvVTSrKRp7/1rJQ1JensRvyvPe3a4ZxhVV6s5Hb1uOweuG1Z9lDxA76zVUmvtAYA8ZKlt1D+gfzHnj/W2m1zE2DYs6YhzblhSXdKTgdsDAAAAAAACMrmI4b3/a0kflPQtSU9J+p/e+8+EbRUAAAAAAAjJ5CKGc+4Fkn5K0qskvUTSuHPuHXvec5tzbt45N3/16tUQzQR6RtwiNsQsYkPMIkbELWJDzCIkk4sYkt4k6Rve+6ve+w1Jn5T0D3a+wXt/r/d+2ns/fezYsSCNBHpF3CI2xCxiQ8wiRsQtYkPMIiSrixjfkvT3nXN155yT9EZJXwncJgAAAAAAEJDJRQzv/cOS/kDSF7T1eNWapHuDNgoAAAAAAARlchFDkrz3v+G9/7ve+9d679/pvV8L3aYitVpeK2ubavnt7y0fukkAckJ+o0jEF4C8UE+AcMi/7IZDNwBbAbu0uq7ZuQVdWlzWqakJnZs5qcnx0X3P5G21vBobTdVHh9RYb6o+MmTuub0Ih/iwp5f8BnqVV3xRO4C4FJGzzFdAOL3mX9XnbbNXYlRJY6Op2bkFXbyypM2W18UrS5qdW1Bjo7nrfe3gPnthXjfc+ZDOXpjX0up6kqt0rET2rkrxEYN2DDfWs+U30I+s88dBqB1AXLrlbLPZGujcKY96AqA/veRfEfN2bJ+9WMQwoD46pEuLy7teu7S4rPro0K7X2sF97HljenD2R/Txf/F6ra5t6tnNtCYXTqj702vxi6lQxWZnDB/JmN+wIbbcyDp/HIQPLkBcuuXs6npzoHOnPOoJOottbkH56qNDetHzx/Tp9/yo/vu/+wl9+j0/qhc9f6xj/uU9b8f42YtFDAMa602dmprY9dqpqQk11ncHYju4f+Wf3Ki7HnhcN/6bh/S+T35Jq4kVQ06o+5P15CPGQhWbnTF8+emVTPmN8GLMjdW1zY7xtbq2mfln8MEFiEu3nB0fGx7o3Cnr+Sh6E+PcgvI9u9HUr7zluc94dz3wuH7lLTfq2Q45nPe8HeNnL/bEMKA+MqRzMyf33QNVH9lzJcZ6U+950w26/f7HdPHKkiRtB9mjOn9mWkfH0hhOTqj70z75aMeG9NzJx87Y2FmoJF0rVCnFUGg7Y/gjn7usD7ztJt1+/2MH5jfCizE36qND++LrA2+7qbcrMTLWDgxm6o4He/5/Fu++pYCWDC6lY4lRt5y9/PTKrvf1eu6U9XwUvYlxbkH5Wi3pV39/92e8X/39x3T+XdP73pv3vB3jZy8yx4BazWlyfFTnz0wfuDlLfWRIr5isRxdkvcorMau24U3Wk48YC1WvQo/9zhh+4ItPSpL+/T/9Ab1isl6JWIxVjLnxvY2W/nDhCd1162t0/QuP6vLTK/rDhSf0cz9yXPURlykP+OACxKVTzt4zc0KfePhbu97X67lT1vNRi0LP+weJcW5B+epjXeJkbH+cHDRv95MLMf4xw2arKqhWc9eCpFuw1GpOK89uRhdkvcrjhLqKO2xnPfmIsVD1wsLY743hq99d0/jYsOS75zfCizE36iNDmnn9K/fF+5HhWuY8iPmDC1BFnXL2yHBNM69/pS5eWR5oMTLL+ag1Fub9g8Q4t6B8vcRJt3lbUl+5EOMfM5z38d+PNT097efn50M3oxTWC3VeBl1RX1nb1NkL87sKwenjk1ku3SutE0PFbeoxNMDY56rEvwolH7NliTU3OsVaY6NpIg8OUEqHWorZlG7BSOlYemC+1lq+GqFIVub9bgLOLeZjFs/JI04GyQVD9SPTLw2f2ehJVf5iNuhfArh0r7vUY8jK2Mf416yqizU3OsWalTwAUJ6qzjvW612scwvKlUecDJILsdUPnk4SoXaQ1dz2d4rgPuywfbCUY4ixxyBSyQ3yAEBVxFDvUplbUKxB4ySGXMgLixhIUvvertPHJzVcczp9fNL8vV3IB2MPkAcAqoN6B2ypUi7Yv1YkUobuK6okLt2LUx55w9jbRm0sB3kAoCr1lnoHS0LmXZVygUWMAsS6OVxqYru3q+ryzBvG3iZqY7nIA6C6qlZvqXewwELeVSUXuJ2kAI2NpmbnFnTxypI2W14Xryxpdm5BjY3O9yO1Wl4ra5tq+e3vrf1PjMnyHiAG3WK517yJCfm7JdYxZvw6o18Au6zW2xTrRorHVFWDjmXXvFtvEiM5S3d5JqBedobNsmJnYVUPyMNBsWx9d/F+kb/PiXGMGb/O6BfANov1NsW6keIxVVUeY9k178aG9H+ef5gYyRFXYhSgl51hs6yU57WazkoxQjsollPdUTlL/qaSm4cdR4xjbPWvmaHRL4BtFuttqLpR5BxLLUzHQWOZNYa65d23lhrESM5YxChALzvDZlkpz2M1vb26ePbCvG648yGdvTCvpdX1aD8sIU4HxXKqOyoflr+p5GaW44hxjC3+NdMC+gWwzWK9DVE3ip5jqYXpOGgss8ZQ57w7oQ9/9msdfy76xyJGAXbuDPu1979V589Md71kKMtKeR6r6awUw4KDYrmXvInJYfmbSm5mOY4Yx9jiXzMtoF8A2yzW2xB1o+g5llqYjm5jubq2mTmGOuXd+Niw/vY7a/t+LjEymEouYpRx6XZ7Z9ia2/7eZdLIslKex2p6yJXiVC6Vj52FcTgslrPmjWV7+/nIcO3AY07lrzhZjyO2MR60/hadd6Hy2uJfeQHsZq3eDlI3+q11Rc+x3f7yXnPivDcyXeOzxxjam3fXDfce91nj3cK5fSiV29jT2gY8WZ7nm8czf9urixevLF17rb0KWOTjd6z1d1VZGYfUn1/drZ8n6iNdjzlUbuYtlePYa5CYLTrvQuZ16rkMIH/91o1Bal3Rc9O+Y1prqtlq6ec/Ns95b2S6xWdjY7AY6jXus8a7lXP7UJz3NldsnHN/R9JHJb1Wkpf0c977i53eOz097efn5zP93JW1TZ29ML8rEE8fn9T5M9NRn2gfJlSgR9jfpWV9L3E7qAjHIUr99HMOuWkiZqs+mXZSdN5FntelBEXWOjt1x4M9/+zFu2/p6f1l/I6y9HMs/TB2/CZqbRUNUuvKnpuM1WViNgdWY8hYrOUpU6daPsJ7JP2R9/6fOedGJdXz+KGpXLrdq1B/Natqf1vDOJSjn35O5S/aqRxHngq/jJm8BlABg9S6sucm6nJ6rMZQ1WPN5J4YzrnnS/pRSf9Jkrz36977/y+Pn13lDXhC3BtZ5f62hHEoR7/9bO2+5X6lchx5KTrvyGsAVTBorStzbqIup8liDFU91kwuYkg6LumqpN9xzi045z7qnBvf+Qbn3G3OuXnn3PzVq1cz/2A2IytXp/6+Z+aEjgxbDb1i9Ru3g9o7Du9906v1W+98neqjQ5XbCKhIKdaXUDGbgqLjoYifn8ImYcQsYlS1uO2l1sQ0t8bU1kFVLWbLkjWGQsda6PMFk3tiOOemJf2/kt7gvX/YOXePpO947//vTu/v9T6sVsursdHMvLlK1veis2azpdX1psbHhnX56RV9+stPaeb1r7R6r7yJ+weLiLv2zzwyUtPS6rrePfcoexcUIEDNMBGz6KzXeCj6/Ye1tcT7ftkTo4DfURb2xChW6rW2n1oT0/l4kW3t8WcTsxHZObbPbjTVakn1sYPHOVReFHy+kOkHWP1z+BOSnvDeP7z9738g6Yfy+uFZLwlqD9DZC/O64c6HdPbCvJZW16P8y1RI39ts6Rd+9xF9/69/Sm/58J/pQ5/9eq7P6E5NUXHXjvvvbbT07rlHC3tmetVxSwV26iUe+sn9POOtsdHU7NwCtQFAofqpNTHNrUW1lc8l6do7tj//sXl9b6MpeR0YQ6HywsL5gslFDO/930j6tnPuxu2X3ijpr8puh4UB6kfoy3v2qvrGM73qNe56HW/GAyjOIPU39JxDbQBQhoNqjaXzV2tCzxEojqWxzXIeY+F8weQixrZ/Jen3nHOPSToh6d+V3QALA9Qri6u0Vd94ple9xF0/4814AMUYtP6GnnOoDQDK0K3WrDy7aer81ZrQcwSKY2Vss57HWDhfMLuI4b1/1Hs/7b2/yXv/0977/1F2GywMUK8sreS1hd54Jja9xF0/4814AMUYtP6GnnOoDQDK0G3T94/95TdMnb9aE3qOQHGsjG3W8xgL5wvDpf2mCLUHaO+mJZZP6Kys5O1U9vOVY9dL3PUz3owHUIxB62/oOYfaAKAMnWrNkZGazv3p5V3vC33+ak3oOQLFsTK2Wc9jLJwvsIhxAAsD1Kv2St7FK0vXXmuv5B0dCzfc7Y1nJAVtRwx6ibt+x5vxAPI3aP21MOdQGwCUYW+tWVnbNHn+aomFOQLFsDK2vZzHhD5fMHs7iRUx7YYs2bi8B4PLGneMN2BHHvkY25wDAHngfCYb5oh0WRjbmPKQpc3EWFnJQzkYb8AO8hEA+kP9BMKLKQ9ZxEhQ6Mt7UC7GG7CDfASA/lA/gfBiyUNuJwEAAAAAAFFgEQMAAAAAAESBRQwAAAAAABAFuze6AAAAAD2YuuPBnt6/ePctBbUEAFAUrsQAAAAAAABRYBEDAAAAAABEYeDbSZxzPyzJe+8vOef+nqSbJf037/2nBm4dAAAAAADAtoEWMZxzvyHprZKGnXN/LOn1kj4v6Q7n3Env/fsHbyIAAAAAAMDgV2L8M0knJI1J+htJL/Pef8c59x8kPSyJRQwAAAAAAJCLQffE2PTeN733DUn/3Xv/HUny3n9PUmvg1gEAAAAAAGwbdBFj3TlX3/7n17VfdM79L2IRAyVptbxW1jbV8tvfWz50k2AQcQLkg1wCgP2ojdXCeIc16O0kP+q9X5Mk7/3ORYsRSWcG/NnAoVotr6XVdc3OLejS4rJOTU3o3MxJTY6PqlZzoZsHI4gTIB/kEgDsR22sFsY7vIGuxGgvYHR4/Rnv/ZcG+dlAFo2NpmbnFnTxypI2W14Xryxpdm5BjY1m6KbBEOIEyAe5BAD7URurhfEOb9DbSYCg6qNDurS4vOu1S4vLqo8OBWoRLCJOgHyQSwCwH7WxWhjv8MwuYjjnhpxzC865/xq6LbCrsd7UqamJXa+dmppQY52VUDyHOAHyQS4BwH7UxmphvMMzu4gh6d2SvhK6EbCtPjKkczMndfr4pIZrTqePT+rczEnVR1gJxXOIEyAf5BIA7EdtrBbGO7xBN/YshHPuZZJukfR+Se8N3BwYVqs5TY6P6vyZadVHh9RYb6o+MsSmOtiFOAHyQS4BwH7UxmphvMMzuYgh6cOSfk3S80I3BPbVak5Hx7ZCuf0d2Is4AfJBLgHAftTGamG8wzJ3O4lz7iclPe29f+SQ993mnJt3zs1fvXq1pNYBgyFuERtiFrEhZhEj4haxIWYRksVlozdIutU59xOSrpP0fOfcx73379j5Ju/9vZLulaTp6WlffjMP1mp5NTaaXGKEXazHbdnIE/uIWWRhKZfLitmpOx4s6kejgqi1tuoIDkfMbiFuwzC3iOG9f5+k90mSc+7HJP3K3gUM61otr6XVdc3OLejS4rJOTU3o3MxJTY6PEtTANvIESAO5DGBQ1BHEiLgNx9ztJClobDQ1O7egi1eWtNnyunhlSbNzC2ps8NgdoI08AdJALgMYFHUEMSJuwzF3JcZO3vvPS/p84Gb0rD46pEuLy7teu7S4rPooj90B2sgTIA3kMoBBUUcQI+I2HK7EKEBjvalTUxO7Xjs1NaHGOqtyQBt5AqSBXAYwKOoIYkTchsMiRgHqI0M6N3NSp49ParjmdPr4pM7NnFR9hFW5srVaXitrm2r57e+tyu47ZA55soUYLQb9Wh5yGYiH1dpIHYElWfOEuA3H9O0ksarVnCbHR3X+zDQ71QbEZju2kSfEaFHo13KRy0AcLNdG6gis6CVPiNtwuBKjILWa09GxYdXc9neCuXRstmNf1fOEGC0G/Vq+qucyEAPrtZE6Agt6zRPiNgwWMZAsNtuBdcRoMehXANiP2ggcjjyJA4sYSBab7cA6YrQY9CsA7EdtBA5HnsSBRQwki812YB0xWgz6FQD2ozYChyNP4sDGnkgWm+3AOmK0GPQrAOxHbQQOR57EgSsxYNqgjwJjsx0cJvTj5ojRYmTp19BjDwBlK3POocaiLHnHGudm9nElBsyy/CgwpIEYqy7GHgCKQ41FWYi1auJKDFxjbcXc+qPAEL+uMcbmTcmjvuTD2rwBwIZuNXZ1nTqBfIWcz5kDw+FKDEiyuYrJI45QtK4xNjakVsuzgp8w6svgLM4bAGzoXmOHtbS6Tp1AbkLN58yBYXElBiTZ/KskjzhC0brF2LeWGvxFPnHUl8FZnDcA2NCtxl5+eoU6gVyFms+ZA8NiEaPi2pdBWfyrJI84ilNMl9ZtxdiJXTH2gbfdpA9/9mv8RT5x1Jfd+slbi/MGABs61dgPvO0mfeRzl03XiZjOYbAl1HzOHBgWt5MUoNXyamw0zT2WZ2+7jgzXtNzY0Ozcgu669TU6NTWhi1eWrr2/vYp5dCxMmPCIo+LlHauWLq3Lcmy1mtP42LD+/T/9Ab18oq7LT6/og5/5qq5+d63U2LdaM4qU5Zi7vSeP/qK+PKffvG3/9cvSvAGkLpb5ol1j733X61QfHb42vz7wxSd1+vjktbZbOhYL5zCxjG+vdh3XWlO1mnTdSD7HGGo+7zYHrjy7OfATTVKNgzxxJUbO2gXw7IV53XDnQzp7YV5Lq+vBV3I7tWt1/bnLoD7yucv6wNtuMvdXSR5xVJwiYtXKpXW9HNt1w0MaHxvWOz76sG459+e6+t21UmPfas0oUpZj7vaeZrOVW39RX7b0m7dczQKUK7b5olZzGh8d1vLquu564HF96ktPXasTR4Zr5o4l9DlMbOOb1b7jum9ey6vreu9/fjS3Ywwxn9dHhnRPh6t5P/aX3xgoZlKNg7yxiJGz0AWwl3aNjw1fuwzqgS8+qQ9+5qu669bX6Gvvf6vufdfr2JgmcUXEqpVL63o5tp0r+F97/1t1/sx0qbFvtWYUKcsxH/SeqvVX0frN29C5A1RNjPWvW5343mbL3LGEPoeJcXyz6HRcv/r7j+n/+rHroz7Gdmzfdetr9NV/+1bddetr9MHPfFXn/vTyQDGTahzkrRKLGGXe3xa6AHbTqV2Xn17ZtRHOA198Unc98Li+/rcrGq/wXyVj1WucFxGrVjZL7PXYQv5F3mrNKFKWY+72np2Lr93+X/Sma96uNQ+tKVzNApQn1vmiU52weCxFnsNkOUez2Cd56HZc17/w6LV/7nSMMexP8r2Nlu564HF9/69/Sm/58J/pgS8+OXDMpBoHeUt+EaPsS3KsfIjbq1O7Pv3lpzpeBvXpLz8VvL3oTT9xXkSsWrm83GoedhJTW/OS5Zi7vWd1bbNy/VW0znl7Qs1Wi8tZAUNSmi8sHktR5zBZz9Es9kkeDnpSTfuf9x5jLLdUFBEzqcZB3pJfxCj7khwrH+KytGvm9a/UxJFR/dY7X3ftMqg/XHhCM69/ZfD2ojf9xHkRsWrl8nKredhJTG3NS5ZjPug9VeuvonXK2/GxYf3ix7/A5ayAISnVP4vHUtQ5TNZzNIt9kodOx/UffuYm/cfPX+56jLHcUlFEzKQaB3kzuX24c+7lku6T9L9Kakm613t/Tz8/q+xLcqzueH9Qu47WnBobTb36RUf10hccN9Fe9KafOC8qVtuXjUriyTYZxNTWvGQ55oPeU7X+KsPevG15z+WsgDEp1T+rx1LEOUzWczSrfTKofce1/XSSD/3vJ7oeY0y3VOQdM6nGQd6sXomxKelfe+//N0l/X9IvOef+Xj8/KMQlOVbvEe7WLqvtRXb9xnnKYx/TscXU1rxkOWZqVjhczgrYlFL9S+lYDtJLPU21T3Yd13XDqo8efIxVn4NSjYM8mVzE8N4/5b3/wvY/f1fSVyS9tJ+fxSU5qALiHECeqCkAkA/qae/oMxzG5O0kOznnpiSdlPTwntdvk3SbJL3iFa/o+v9zSQ4syRq3vSLOUZSiYha2xVxTiFnEiLhNV8z19CBFxmyqfYb8mLwSo805d1TS/ZLe473/zs7/5r2/13s/7b2fPnbs2IE/J/ZLcmJ4xBCy6SVuexV7nFdBjLlcZMzCpnacql1CvKKqKcQsYlRW3MY4D6UgxXO0omP2sD4jlqvN7JUYzrkRbS1g/J73/pOh2xNK+xFDs3MLurS4rFNTEzo3czLIEx8A9I9cRgyIUyBd5DdSQSzD5JUYzjkn6T9J+or3/kOh2xNSLI8YAnAwchkxIE6BdJHfSAWxDJOLGJLeIOmdkn7cOffo9tdPhG5UCDE9YghAd+QyYkCcAukiv5EKYhkmbyfx3v+Fnrsbt9Lajxi6eGXp2mvtRwzl9fxqAMUjlxED4tSWqTse7Pn/Wbz7lgJaghSQ30gFsQyrV2JgG48YAtJALiMGxCmQLvIbqSCWwVKVcVYeMdRqeTU2mjzmKCDGIG5Wchn9qUr+EadAuizkd1VqKYplIZaLQo5kwyJGBNqPGJIU5BIpdgAOjzFIQ+hcRn+qln/EKZCukPldtVqKYqU4V5Ej2XE7CQ7FDsDhMQZAOOQfAAyOWgocjBzJjkWMDlotr5W1TbX89veWD92koAbZAZi+zAe7MKepW35UOW8sHruV/LPYNwCqqZ96xPlktfU6hlUccyvnGzFgEWOP9mU8Zy/M64Y7H9LZC/NaWl2vROJ0094BeKf2DsAHoS/z0+8YwK5u+dFstiqbN1ZrhoX8s9o3AKqn33rE+WR19TqGVR1zC+cbsWARYw8u49mv3x2A6cv8sAtzeg7Kj6rmjdVjt5B/VvsGQPX0W484n6yuXsewqmNu4XwjFmnsgpKjql3Gk2UH3H53AK5aXxaprF2Y2RG5PN3yY3xsuLJ5Y7VmWNgFfdDLsMlrAHnptx5V5XySmrtfr2MYy5jnPdYWzjdiwZUYe5R1GY+F+7x6uVSrvQNwzW1/z5BMXBKVr37GoBed4uGZ1TU1W63K3ItYpm75sbq2WYm86VQDLdeMovPvMFyGDcCKQWp16ueTg9RcC58NitLrGOY15kX2aVHza+jzjViwiLFHGZfxWDmpLPpSLS6JikuneHj33KO6/PQqH3wKcFB+pJ433WrgkeFa8sfeLy7DBmBF2fNUTPNivzXXymeDovQ6hnmMedF9yvwaFreT7FHGZTw7g17StaA/f2a61OccF32pFpdExaVbPFz/wqPBYjRlB+VH6nlzUA1M/dj7VZXLsAHYV/Y8FdO82G/NtfLZoCi9jmEeY150nzK/hsWVGB0UfRmPhaBvtXwpl61zSVQ8ul26d/npFUlpFGZrl2p2y4/U8+agGtjp2K2NWyipX4YNoDyD1tWy56lY5sV+a66FzwZF63UM+x3zdmzXR4d0162v0a0/+JJr/y3PPmV+DYtFjABCB3378qrf+Ytv6ANvuymKy/NQvE6X7n3gbTfpI5+7LCn+wpz6pZox6aUGMm6DiekybADloK4Wp+9b//hAnIu9sX3XA4/rV/7JjdcWMvLsU+bXsOK/PilC7aCfnVvQpcVlnZqa2Bf0Re5svPPyqstXV3XXra/R9S88qsb6psZH7a5uo1h7L91beXZTH/vLb+hTX3oqicLcWE/7Us2YZKmBbalfYnuYQeeCmC7DBlCOqtXVMp8W0vetfz3Mi9jSaVw7xfbt9z+mu259ja5+dy3XPmV+DSu9ShWBw4K+vYq4t5BNjo/mkhg7L1l74ItP6oEvPqnhmtPX3v9W1Vw8iccjrLLppZ/al+5J0tGxYf3cjxzXv3zjq6Pv31bLqz6W/qWasehl4q/CJbbd5DUX7M3rXttAnQXSUqW62k8dzWPxuNeaywfi3nQd16OjHWP71S86utW3OfdplrFmHi0Gt5MEctB9XkXvdpvCJWtcCpnNIP0Uy/2nWTQ2mvrWUiP6uE9J1vhKoV71K/TO59RZIE1Vqqu91tGQdS+l866idRvXg/b7C9GnzKPF4UoMg4peIU/hkrWqXQrZL/ppS310SB/+7Nf0gbfdpNvvf2xH3J+IKu6rKIV61a/Qfy2lfsRp6o4HQzchNykdiyVVqqu91lHqXhwOGldLsU08FYfeM6i9Qt4OeGn3KuKgUrhkLfTJfSzopy2N9ab+9jtr+uBnvnptD5hvLzc0zl86zEuhXvWr6LngMNQPIE1Vqqu91lHqXhy6jev3NlqmYpt4Kg63kxhUxm63sV+yVqVLIQdBP21p59TV767plnN/rnd89GGNjw3rumEmkRjEXq/6FXrnc+oHkK6q1NVe6yh1Lw4Hjaul2CaeimP2Sgzn3M2S7pE0JOmj3vu7AzfpQHlu2lKlFfJ+VelSyE6yxlvV+6mNnEKMsmwCXeRmYdQPACGEPKem7sXB8nndzviVl37zHT+kX/z4F4innJlcxHDODUn6iKQ3S3pC0iXn3APe+78K27LOiniayCC7yVeB5eJVtF7ircr9tBc5hRh1i9uin2LV/t3UDwBlCn1OTd2Lh8Xzus7xe0L/6Z9P67oR4ilPVm8n+WFJl733V7z365I+IemnArepq9A7yFeVpcvFytRrvFW1n4CUlTXvUD8AlMnCOTV1D/3qHL+PquVFPOXM6iLGSyV9exx2+QIAACAASURBVMe/P7H9mkls2oIyEW8AqAMAUkRtQ8yI3/JYXcTotES164G6zrnbnHPzzrn5q1evltSszti0BVnlEbfEG8pkqdbiOdSB7ohZxIi43UJtiwcxux/xWx6rixhPSHr5jn9/maQnd77Be3+v937aez997NixUhu3V+gd5BGPPOKWeEOZLNVaPIc60B0xixgRt1uobfEgZvcjfstjYxeU/S5JerVz7lWS/lrS2yX9H2Gb1B2bAKFMxBsA6gCAFFHbEDPitzwmFzG895vOuX8p6dPaesTqb3vvHw/crANZ3CEX6SLeAFAHAKSI2oaYEb/lMNuz3vtPSfpU6HYAAAAAAAAbrO6JAQAAAAAAsAuLGAAAAAAAIAosYgAAAAAAgCiwiAEAAAAAAKLgvPeh2zAw59xVSd/c/tfvk/RMwOZYQl/slqU/nvHe31xGY/bEbdURq90d1jfWYpaxpA/M1Fpiti/0x27t/ghdaxmXLfTDFjN1Vir0nDbG8abNg8kUt0ksYuzknJv33k+HbocF9MVu9IddjE13sfVNbO0tQtX7ILbjj629RaM/drPSH1baERr9sKUq/RDjcdLmcnA7CQAAAAAAiAKLGAAAAAAAIAopLmLcG7oBhtAXu9EfdjE23cXWN7G1twhV74PYjj+29haN/tjNSn9YaUdo9MOWqvRDjMdJm0uQ3J4YAAAAAAAgTSleiQEAAAAAABLEIgYAAAAAAIgCixgAAAAAACAKLGIAAAAAAIAosIgBAAAAAACiwCIGAAAAAACIAosYAAAAAAAgCixiAAAAAACAKLCIAQAAAAAAosAiBgAAAAAAiAKLGAAAAAAAIAosYgAAAAAAgCiwiAEAAAAAAKLAIgYAAAAAAIgCixgAAAAAACAKSSxi3HzzzV4SX3zl8VUa4pavnL5KQ8zyleNXKYhZvnL8Kg1xy1dOX6UhZvnK8SuTJBYxnnnmmdBNAHpG3CI2xCxiQ8wiRsQtYkPMomxJLGIAAAAAAID0sYgBAAAAAACiwCIGAAAAAACIQtBFDOfcbzvnnnbOfXnHaxPOuT92zn19+/sLQrYRAAAAAADYEPpKjI9JunnPa3dI+hPv/asl/cn2vwfTanmtrG2q5be/tzJvmgr0jbgDqoncRwyIUwDIF3W1N8Mhf7n3/s+cc1N7Xv4pST+2/c8XJH1e0u2lNWqHVstraXVds3MLurS4rFNTEzo3c1KT46Oq1VyIJqECiDugmsh9xIA4BYB8UVd7F/pKjE5e5L1/SpK2v78wVEMaG03Nzi3o4pUlbba8Ll5Z0uzcghobzVBNQgUQd0A1kfuIAXEKAPmirvbO4iJGJs6525xz8865+atXrxbyO+qjQ7q0uLzrtUuLy6qPDhXy+5C+LHFL3MGSMmottpD7+SBmi0WcFoO4RWyI2fxQV3tncRHjb51zL5ak7e9Pd3qT9/5e7/2093762LFjhTSksd7UqamJXa+dmppQY51VMfQnS9wSd7CkjFqLLeR+PojZYhGnxSBuERtiNj/U1d5ZXMR4QNKZ7X8+I+m/hGpIfWRI52ZO6vTxSQ3XnE4fn9S5mZOqj7AqhuIQd0A1kfuIAXEKAPmirvYu6Maezrk5bW3i+X3OuSck/YakuyX9P865n5f0LUk/E6p9tZrT5Piozp+ZVn10SI31puojQ2ywgkIRd0A1kfuIAXEKAPmirvYu9NNJZrr8pzeW2pAD1GpOR8e2uqn9HSgacQdUE7mPGBCnAJAv6mpvLN5OAgAAAAAAsA+LGBXSanmtrG2q5be/t3zoJgEQudkr+gupIJYBVA11D3ngWpVAWi2vxkaztPueWi2vpdV1zc4t6NLisk5NTejczElNjo9yvxU6KjtGq6qqudlvfFW1vxBWEfWQWAZQNWXXPc5l08WVGAG0E/jshXndcOdDOnthXkur64WuRDY2mpqdW9DFK0vabHldvLKk2bkFNTZ4dA/2CxGjVVXF3BwkvqrYXwirqHpILAOomjLrHueyaWMRI4AQJy710SFdWlze9dqlxWXVR3l0D/bj5Lo8VczNQeKriv2FsIqqh8QygKops+5xLps2FjECCHHi0lhv6tTUxK7XTk1NqLFOImM/Tq7LU8XcHCS+qthfCKuoekgsA6iaMuse57JpYxEjgBAnLvWRIZ2bOanTxyc1XHM6fXxS52ZOqj5CImM/Tq7LU8XcHCS+qthfCKuoekgsA6iaMuse57Jpc97Hf1/Q9PS0n5+fD92MzEJt5sXmNpmU1iGW45YN58o1YG5GF7ODxhe1LAmlDFgeMVtkPSSWoxJdrUXlmYzZsuoe57LRyjQ4PJ0kgFrNaXJ8VOfPTJd64lKrOR0d2xry9negk1AxWlVVy81B46tq/YWwiqyHxDKAqimr7nEumzZmzEA4cYF1xCiKRHwhJsQrAMSH2p0u9sQAAAAAAABRqMQiRqvltbK2qZbf/h7584FTOx7ko5e4IIaAzsiN59AXxaBf96NPAOxVxbpQxWPuV/LX1aS2qUtqx4N89BIXxBDQGbnxHPqiGPTrfvQJgL2qWBeqeMyDSP5KjMZGU7NzC7p4ZUmbLa+LV5Y0O7egxkacj9dJ7XiQj17ighgCOiM3nkNfFIN+3Y8+AbBXFetCFY95EMkvYtRHh3RpcXnXa5cWl1UfjfM57KkdD/LRS1wQQ0Bn5MZz6Iti0K/70ScA9qpiXajiMQ8i+UWMxnpTp6Ymdr12ampCjfU4V7VSOx7ko5e4IIaAzsiN59AXxaBf96NPAOxVxbpQxWMeRPKLGPWRIZ2bOanTxyc1XHM6fXxS52ZOqOYU5aYpnY/npOojrNJVWZa4aG8WdGSkpntmThBDwB5F1NdYN+lirilGyv3ab6yn3CcA+lPFutDPMcd6jpEH5338Bzs9Pe3n5+e7/vdWy6ux0VR9dEiNtaaarZZ+8eNfiHbTlF3Hs95UfWSo77bn+bMSUdrBHxa3vTpoLPduFjT749frn7/hVTp63fCu9xIPUYo2Zi3Ku75a2KSr32MquB6U0gF5xmxe/ZFinR001iPpE2otYhN1zMZQF/JuYy8/z8o5RgEyNT75KzEkqVZzOjo2rJpzkpN+8eNfiHrTlJ3Hc3RseOAT7LMX5nXDnQ/p7IV5La2uR7eKV+VVyJ0Oiou9mwV96LNf1y/87iNqrDevvTeVeOiGOEEWedVXycYmXYPkdbe+qGIu5Vkf84yxrIoes0FjPUSfALDNel1oNlt6ZnUt1/PmXo7ZwjlGSGYXMZxzv+yce9w592Xn3Jxz7ro8fi6bpjwnheBP/YN3XrLEfQrx0A1xghAszDd553VVcynm+ljGmFmIdQAoS6vltbre1Lvn/v/27j7Irqs+8/3zO/0iu1tkEnVsYrCdRpHtO7wYC1oQXSYkEAIGcw0zXO6gCqC8jJyknCtTBGI7piqeO0NiF4SAKlQYGxJEYERCTBLXGMdAgFCkhKM2EibGMShCgGOCRCsZW33sfjvr/tHntE93n5e9z9l7r7X2/n6qVC21293rrPWs3969zt5rH/N2XKh63Q1yEcPMni5pv6QZ59yzJY1IekMW3zvETVN8vatVhvDHfGJZpCS5LyoPPvJOTuBDCMebrOd1t7k0v1juKzJiPl4WUf+6Zf2JpZXKXbUDoPzqSyua3DKa+LiQx7lvCOcYPgW5iNE0KulcMxuVNCHpkSy+aWgbxfh8V6sM4Y/5xLJISXJfRB585Z2cwIcQjjdZz+vuc2m01FdkxHy8LKL+dcr6B974PM0vLFfuqh0A5TcxPqLjp84mOi7kde4bwjmGT0EuYjjn/lnSuyV9R9L3JP1v59yn27/GzK4xs1kzmz19+nTi712rmaYmx3X73hl9452v1O17Z7xugOLzHeIyhD+2E8tBczusJLkvIg++8h5bTkLiK7NlEMLxJut53W0uHT91Npirm/LIbMzHyyLqX6esj9Rq2u/xUuvYUGsRmypntr64onv+4Xu69XWXrzsuvG/PFZuOC3md+4ZwjuFTkE8nMbMfkXSHpP8s6d8kfULSnzvnPtrp62PexbnhnC696W4tt63GjdZM33jnK1c3Is3750ew828vOezMG/VOzsPKOw++8l7iHZylimcW/eX9xJVbX3e53v3ph/Spr30vzVyu7NNJiuar/vk+v8kBtRaxIbM5adXVQ/d+W6949gXacf5WzS8sa3J8RCMj668RKGEtzFuiThnNuxUDepmkbznnTkuSmX1S0v8pqeMiRsxa75AcPjG39rnWOyRbt+Q/PK1dcCUV8vOy1r4KGduJZYjyzoOvvJMTVFmW87o1l2578/M1MT6q46fO6t2ffkh3fvUR7d4+Vdixy4dYj5e+6p/v8xsAyEurrv7ST21fq6vdniZCLcxHqD33HUk/aWYTkh6X9LOSSrm817pEdeM7JDFcohqKWE8sq8hn3skJkI1azTTZ3APj5jsf0JGTZ6K6vaKKfNQ/zm+qa/qGu1J9/clbrsqpJUB+ktZVamE+gjyTd87da2Z/LukrkpYlHZV0m99W5YN3iFEl5B0oB+Yy+iEjAEAtzEuQixiS5Jz7bUm/7bsdReAdYlQJeQfKgbmMfsgIAFAL8xDk00kAAAAAAAA2YhEDAAAAAABEgUUMAAAAAAAQBRYxAAAAAABAFFjEAAAAAAAAUWARA9FqNJzOLiyr4ZofG853k4JEPwEYVNXqR9VeLwAgXxxX8sEzXiqu0XCqL61E99ziRsNpbn5R+w8d1ZGTZ7RrepsO7NmpqcnxKNpfFB/9FGumgCrrNG8lVarO+jquUDMBIF69aji/r+SHKzEqrDWx9h2c1aU33a19B2c1N7/Yc4UwlNXE+tKK9h86qsMn5rTccDp8Yk77Dx1VfWnFS3tCVXQ/DZKpvISSVSB03ebtE8tP1o9XPecC3Xz1s7Rtclzzi+WcTz6OKyHVzDKh/gMoQr8a7vv3lTLXQhYxKiztxArpZGtifERHTp5Z97kjJ89oYnyk8LaErOh+8l2sW0LKKhC6bvO20VitF1c/92l628sv0813PqDL3nG3rvnIfaWcTz6OK6HUzDKh/gMoSr8a7vP3lbLXQhYxKiztxArpZKu+uKJd09vWfW7X9DbVFznxa1d0P4WyuBRSVoHQdZ23W0a0a3qbrn3JDl1/x/2ln08+jiuh1Mwyof4DKEq/Gu7z95Wy10IWMSos7cQK4WSrdVnUxPiI/sebnq+3vuwSjdZMu7dP6cCenWv3cWPVxNiIDuzZqd3bpwrpp26Zmi/4UrYQsorslPlyyBB0PRYsrOjAnp3acf7WSsynouulxIJ8Hqj/AIrSr4b7OK60+L4KJO/zNjb2rLDWxNq42Uy3idWaqIdPzK19rjVRt27JP0qdNsd5354rdO1Ld+jxpQaboXVQq5mmJsd1+96ZQjaN65Sp973hCv3xl76lA587XtiGRr6ziuywKVb+uh4Lxkc0MT6i+cXlSsynouullP44jP7qC13q/8KKtp5TnrwC8K9fDfdxXGnxdS5c1HmbORf/O1ozMzNudnbWdzOilGZXdN+/TJxdWNa+g7PrJuPu7VO6fe9MlpOxsN+Kyprb9kzNLyzrj7/0Lb3ns99c++85jFnHNlToF99SZ7ageV95HnZXLyS3MdRZnk6Srfriss7ML+rtn7h/La/vev3l2jY5ronxoWpGqWttlqZvuCvV15+85aqcWlJ5ZLYAodZwX+fCGZy3JWocZ4AVV6vZWqD6BcvnaqLEJaKxaM/U5JZRHfjc8XX/vYgx851VZId5X4xexwLmU77SHIfR3zljI3r3PQ/p5qufpR3nb9XxU2f17nse0nv+8xW+m4Yu0i56SIMtfBT1c1AtodZwX8fuos7b2BMDqbQmas2aHws8ieXe4fj4HDOfWUV2mPdhYD4hFvXFFX3/0QW94r1f1E/81qf0ivd+Ud9/dIGaAaByfBy7izpvYxED0fC5OQ4Gw5hhWGQIQBrUDADwp6gaHM41L0AfXNIcH8YMwyJDANKgZgCAP0XVYK7ECFQej6Ypw2MKuaQ5PqGMWcj5D7ltaeT1OkLJkA9lyUZs6Pfh+O6/KtcMoCqKrDO+a1psiqjBwV6JYWY/LOmDkp4tyUn6JefcYb+tKkYeu8lW7GkNwDoh5z/ktqVRltcREvrUD/p9OPQfgLwVWWeoaWEK+UqM90n6a+fc/yHpuZIe9NyewtSXVrT/0FEdPjGn5YbT4RNz2n/oqOpLg2+Iksf3BGIRcv5DblsaZXkdIaFP/aDfh0P/AchbkXWGmhamIK/EMLMfkvRiSb8gSc65RUmLPttUpDweTcNjClFlIec/5LalUZbXERL61A/6fTj0H4C8FVlnqGlhCvVKjO2STkv6YzM7amYfNLNJ340qSh6PpuExhaiykPMfctvSKMvrCAl96gf9Phz6D0Deiqwz1LQwhbqIMSrpeZL+0Dm3U9K8pBvav8DMrjGzWTObPX36tI825iaPR9PwyLEwlDm3IQs5/yG3TUqe2dBfR4zo08EMW2fp9+HQf4Ph/ACx8ZnZIusMNS1M5lx4u6ua2Y9J+rJzbrr575+SdINz7qpOXz8zM+NmZ2cLbGH+Gg2n+tJKpo+myeN7llBhHVLG3IYs5PwP2bZgMhtyH8eqxH1ayIsYtM6WuN8LUdL+C6bWhm76hrty/xknb+n4K0FPg7RrkJ8TkFJntsg6U9KaFqpEHRvknhjOuX8xs++a2WXOuYck/aykr/tuV5Faj6aRtPYxxO8JxCLk/IfctjTK8jpCQp/6Qb8Ph/4DkLci6ww1LTyh3k4iSf+vpI+Z2f2SrpD0O57bg8jwTOfqYuwB5gHCRj4BIHtVqa3BLiU5545JmvHdDsSJZzpXF2MPMA8QNvIJANmrUm0N+UoMYGA807m6GHuAeYCwkU8AyF6VaiuLGCglnulcXYw9wDxA2MgnAGSvSrWVRQyUEs90ri7GHmAeIGzkEwCyV6XaGuyeGMAwWs903nhPGM90Lj/GHmAeIGzk048KPmK0cPQxfKpSbWURA6VUq5mmJsd1+94ZnulcMYw9wDxA2MgnAGSvSrWVRQyUFs90ri7GHmAeIGzkEwCyV5XamvmeGGb2kay/J+JVlWcVA1li3qATchEOxgIA0qFuIktDLc+Y2Z0bPyXpJWb2w5LknLt6mO+PuLWeVXzo3m/rFc++QDvO36qzC8uaHB/RyAh7yqKcGg2n+tLKwJfxVekZ30iuWy62TYzp8eVG6S8bDQlztLNhax+A8qJupkM97W/Y3yQvlPSopPdI+r3mn8fa/o4Kqy+t6NC939Zrd16om+98QJe94279yp/cp7n6IquvKKXWQXrfwVldetPd2ndwVnPz6fJepWd8I7lOuTh077c1Vx8ub0iPObpZFrUPQHlRN5OjniYz7CLGjKT7JN0k6X87574g6XHn3N865/522MYhbhPjI3rFsy/Q9Xfcv65oXXfoGEULpZTFQbpKz/hGcp1y8YpnX6DrDh3jpLBgzNHN+AUFQC/UzeSop8kMtYjhnGs4535f0i9KusnM/kBsFoqm+uKKdpy/laKFysjiIF2lZ3wjuU65oL76wRzdjF9QAPRC3UyOeppMJhsTOOceds69XtLdkj6axfdE/CbGRjS/sEzRQmVkcZBuPeN79/YpjdZMu7dPlfYZ30iuUy6or34wRzfjFxQAvVA3k6OeJpPpVRPOubsk3ZXl94wFG7BsVquZJsdH9L49V+i6Q8fWbeRD0RoOeQtT6yC9ceOqNHmv0jO+kVynXJwzUqO+DmmQWsoc3SyL2gegvKpUN4c9R6eeJsOtHxlgx93uRkZq+tHJLZUoWkUhb+HK6iBdlWd8I532XEyMjWhuflEfv/c7uvnqZ2nH+Vs133z6E3UgmWFqKXN0vSr9ggJgMFWom1mco1NPk+E5lxnotmv8/KKfZyG3P4f5sSeWtNJoeH0ec6to1az5kUk4lK4b/iyuBPnc7V7PBS/jM8PJezzyyF9RmW7Vgfd89pt6xXu/qJ/4rU/pV/7kPj2+3Mjl5/UT41wuy+ZpRfV9v58TW+2LMbMAwtNeS+YXl3Xo3m8PfVzxWU+T1kbfNbScy2AF27gBy9XPfZpeu/NCXfOR+wp/p7zTCuCtr7tcf3n0Ye154Y/zbn0JdNvw59zxEb3xg/cGdVVGrxVpSVxRAm/yuKKpyKukQtr4K9arw0Lqw0EV1fexjnE3ZXs9APzo9nvX8dPzuvOrj0iK67iStDaGUEO5EiMDGzdgufYlOzY9VrSod3c6vbN0/R336xXPviDKd5iwWbcNf46fOhvcO4m93uksy7ugiFMe+Ssy0yFt/BXrXA6pDwdVVN/HOsbdlO31APCj2+9d175kx9rXxHRcSVobQ6ihLGJkYOOOuz4fe9ftnaVWm2JZCUR3nXZ4vvV1l+v9nz8uKawV317vdJbhXVDEK4/8FZnpkHZ6j3Uuh9SHgyqq72Md427K9noA+NHr964YjytJa2MINZTbSTKwcQOWJxZX9Nm3/rQu2jah46fO6v2fP67Tjy2ovriS+0Y2rXeWDp+YW/tc61361kpgWTfTqYqNefvOXF3v/vRDa5ethTTO3fLYWpHu9t+yaDtPcAmb7/Hplc1B85fH9+wmpI2/inzdWQqhD4edB0X1faxj3E3ZXg8QOt/H/Lx0ryXL+sY7Xxnda01aG0OoocFWajMbkTQr6Z+dc6/23Z5+WhuwNBqrm7rc+Mmvrd0j9K7XX66nbBktZBWu02N5Wnti+FwJLGvx8qU9b5NbRnX6sQWN1izxY5iKGo9+j4nK6xFSIdyrh+5CGJ88HmFW9GPR8tjpfZDaEPPj4Hzulp/FPCiq7zv9nA+88XmSkxrORXdcjzmzLdM33OW7CUAiIRzz89KtlkyOP7kpZ0yS1saJsRF94I3P07/Wl3TRtgl990xdPzIxVmgNNefC3I3ZzN4qaUbSD/VbxJiZmXGzs7PFNKyPswvL2ndwdt3K1O7tU7r9zTPaek4xQW4/CZ1fWNbE+IgeX2p4O8GIrHgV1qCscpv2l46ix6NX+/JaTOk6D/fORHdASSC6zIYyPnnkL+YF22FqwwCvu5BOCen8YKOs5kFRmWv/OU8srWh+YVn7Dx2L4bjeUaiZlZLltqhFjJO3XJX6/ymibUW1K+3PKeJnpBBEZkM55ucl5uN+J0lez+r5wsKGY8AVmprcksVrT/QNgtwTw8wulHSVpA/6bktaXe8R2jLcylSax9i0P5bnKeeMaaRWG/rxPMM8RieEzV/KoNsYpH0MU9Hj0at9eT1CKoR79dr5fgxVaEIZn6T5azSczj7RHL8nllVf7D6GsT1mst0wtSHm1z2sQed3VvOgqL5v/zkNJ+0/dKxvVkKufVXOLFCkUI75SQxSs7KuJb7rZpLXs3q+sPEYcIyNPSW9V9JvSvLzwPsh5LHbeevdsX0HZ3XpTXdr38FZzc0vFhbqYX9+TMUrVFlmoArjEdJTB3zP3xCFND79tN5t2PeR5vh9ZFZn5hf12BNLpRvDKtSGrA0zv2OaBxslyQq1D4AUT60LoWaF0IYkQjhfCG4Rw8xeLemUc+6+Pl93jZnNmtns6dOnC2pdf3nsdu77SoZhf34sxasIg+Y2ywxUYTxCeuqA7/k7rDxqbUjj00+ndxve/on79a/1pWjGMKmy1IYizw+Gmd8xzYONkmQl9tpXtFDPa4FukmY2lloXQs0KoQ1JhHC+EOKNSC+SdLWZvUrSOZJ+yMw+6px7Y/sXOeduk3SbtHofVvHN7CyP3c6LWu3qdg9Ut59/7lhNZ5t7bvR6nWXYQCsrg+Y2ywxkNR4h3wOYdh7m+VpCWK0exrC1tlvf+n4qRFLdxu+ibROy8Jo7lEFqQ4h1oMjzg2Hmd6d5cO5oLbj+7CRJVkKvfaFlN9TzWqCbpJmN5Zg/SM3Kuo6EXjdb0pwv5FVrg1vEcM7dKOlGSTKzn5H0to0LGKHLerfzIh5j02tDt/rS5p+//6U7NDe/qOsSbOoVS/EKWZYZyGI8YtisNek8zPu1hPAYKl/69a2vp0Kk0W38vnumrh99ypag257WIIt/odeBvA07v9vnwcTYSDT9mSQrIdc+sgsUK4ZjftqalUcdCblutkt6vpBnrQ3udhJsVsRlWL0uX+r083/hRc/QdQk29WoZdNMb35vbhCLrDAy7CVEsl7sl8cTy6i77H/0vL9Rd+39K5z1lS6avJZbLKPMQek6S1JfV8bti3fi96/WXF/4osaKkqQ2hj28Rspzf7f35qudcoJuvfpa2TY5rvsdGsj71y0rItY/sAuWSxe8LaWtWHnUk5Lq5UfINQPOpteEs6XTgnPuCpC94boZ3RVzJ0OvypZp1+PkFXO7EOyVPCu1qllgud+un0XCaX1jWjZ/82lrGbn3d5XrPZx7K7LWENnZFCjknSevL6vht0e1vntHElhHVF1ZUq0nnjFZjDHsJeXyLkuX8bvXn1c99mt728st0/R33R33sC7n2kV2gPLL6fSFtzcqjjoRcNweRZ63lSoxI5P0osH4btGz8+UVs6MI7JeuF9Di4EDb0yUKnTRuvv+N+veVll2b6WkIauyKFnJM09aVWM209pzl+54xqYrw6Y9hLyONbpKzmd6s/r33JDl1/x/2lOPaFWvvILlAeWf6+kOpqxJzqSKh1cxB51loWMSAp/eVLRVzuxDsl4YrpcrdeumXs4qmJ6F5LiELOCfVleCGPb4xa/bnj/K1kM2dkFygPX8dz6kh/efZR0LeToDhpL18q4nKnWDa3qaKyXO7WNWMLK9p6DhkbVsg5ob4ML+TxjVGrP+cXl8lmzsguUB6+jufUkf7y7COuxMCatJcv5X25EyucYSvD5W5dM8Y7npkJNSfUl2yEOr6xqtVMk+OjZLMAZBcoB5/Hc+pIf3n1EUv6CBYrnMgbGasuxh6hIpsAkBw1s5pYxEDQYniuNOJGxqqLsUeoXXgEQwAAIABJREFUyCYAJEfNrB5uJwEAAAAAAFFgqaqDRsOpvrTCJUkAckWt2Yw+QQzIKYCsTN9wV+r/5+QtV+XQkrBQZ9ELixgbNBpOc/OL2n/oqI6cPKNd09t0YM9OTU2OM3EAZIZasxl9ghiQUwDIF3UW/XA7yQb1pRXtP3RUh0/MabnhdPjEnPYfOqr60orvpgEoEWrNZvQJYkBOASBf1Fn0wyLGBhPjIzpy8sy6zx05eYZHLgLIFLVmM/oEMSCnAJAv6iz6YRFjg/riinZNb1v3uV3T21RfZOUPQHaoNZvRJ4gBOQWAfFFn0Q+LGBtMjI3owJ6d2r19SqM10+7tUzqwZ6cmxlj5A5Adas1m9AliQE4BIF/UWfTDxp4b1Gqmqclx3b53ht1wAeSGWrMZfYIYkFMAyBd1Fv1wJUYHtZpp65ZR1az5MeGEaTSczi4sq+GaHxsu55YCYWEOpDNorSmzEPuEXGOjEHNaZcxRoHyos36FXle5EiMjPAoIVcccQBmRayBszFEAyFYMdZUrMTLCo4BQdcwBlBG5BsLGHAWAbMVQV1nEyAiPAkLVMQdQRuQaCBtzFACyFUNdZREjI8M+Cij0+46AfngcVnfM73jFkGvyhTJJm+cY5igAJBHK8TyGuhrkIoaZXWRmnzezB83sATO7zneb+hnmUUCt+472HZzVpTfdrX0HZzU3v8iJKKLC47A6Y37HLfRcky+UySB5Dn2OAkASIR3PY6iroW7suSzpN5xzXzGzp0i6z8w+45z7uu+GdTPMo4Da7zuStHbf0e17Z7R1S6hDBKzH47A6Y37HLfRcky+UySB5Dn2OAkASIR3PY6irQZ7hOOe+J+l7zb8/ZmYPSnq6pGAXMaQnHwUkKVXYYrjvCEhi0DlQZszv+IWca/KFMhk0zyHPUQBIIrTjeeh1NcjbSdqZ2bSknZLu3fD5a8xs1sxmT58+7aNpmYnhviNko0y5RTKxz28yG7bY85UHMhuvKueZ3CI2ZDZbVa5/gzDnwr1v1sy2SvpbSe90zn2y29fNzMy42dnZgX5Go+FUX1rxeqlMDM/irZDCOnyY3IYshDkVkgLmd+kyS4aSi/j4UUjjylpny2qYPBdQN4KqtdM33FVQa8J08parUv8/g/RZ2p9T1LgkbFdQma2iNHUp4uN51hK92PCuDWkyszFJd0j6WK8FjGGEEpYY7jsCkghlToWE+Z0OGUqHfKFMBs0zdQNAaNLWJY7n6QR5O4mZmaQPSXrQOfeevH5O+wYqyw23toFKfan4y3Za9x3VrPkx58CG8ggflEtIc6oTX7kven7HrFOGDt37bc0vUq+6IV/54DjpxyB5Dv3YA6A4odTuQeoSx/PkglzEkPQiSW+S9FIzO9b886qsf0hoG6h0k/VkDOkRPiiXkOdUCLkP5cAaso0Zuvq5T9Nrd16oaz5yH/WqIOQ0m3pBPxYn5GMPgHx0qrEhnOu1UJfyFeQihnPuS845c85d7py7ovnnU1n/nBg2UMljMlbpHQtOIosV8pzynftuc3llpUFG22zM0LUv2aHr77g/9bgx9wcT0gmgT8PWi7z6kVx3FvKxB0D2utXY+mI253pZ1FrqUr6CXMQoysTYiA7s2and26c0WjPt3j6lA3t2amIsnBWyPH7xqsrKICfjxQt5TvnOfbfbJObqZLTdxgztOH9r6nFj7g/O92JfKIatF3n0I7nuLuRjD4DsdauxE1uGP9fLqtZSl/IV7MaeRYhhA5U8fvFqrQwePjG39rnWymCIzwEeVHuBk7RW4G7fO1Oq1xmSkOeU79x3msuvePYFuu7QMTLaZmOG5heWU48bc39wvhf7QjFsvcjl2E2uuwr52AMge91qbH1h+HO9rGotdSlflb4SQwp/A5U8LkWqysogJ+N+hDqnfOe+01we5CqDKmjP0OT4aOpxY+4PjstfVw1bL3I5dpPrnkI99gDIXrcaW6tp6HO9LGstdSk/1V66j0DrRGrj43mG+cWrKiuDvt95R1h8577TXB7kKoOqGWTcmPuDy+OYE6Nh60Ue/UiuAWBVtxp7zuiIzhkdGepcj1obB0YiJ42GU31pZehflvL6xau1MiiptBOSk/H4ZDVvuvGZ+05z+dzRWuUyOsgYpx035v7gfC/2hWSYepFHP8ac67xrO4Bq6VdjhznXG7bWUu+KUc7fXj1rbQizMfxTk+MDL2SUfcEhD5yMxyXreROiTnO5ShktaoyZ+8PhmJONrPsx1lxXobYDKF5ex6phai31rjiV3xMjD+zuHg7uRYtHVedNlTJa5BhXqV9RHTHmuqq1HUC8Bq211LvisIiRAzbfAtJj3pQfYwxUD/MeQFVQ74rDIkYO2N19eI2G09mFZTVc82PKZzMjPmWbN2R4s7KNcSjIGkKWdN6TYwCxi/k8J7YazCJGDnw/yjF2rfvJ9h2c1aU33a19B2c1N78Y/GTCcMo0b8hwZ2Ua41CQNYQuybwnxwDKINbznBhrMDt25SDWzbdC0X4/maS1+8lu3zvDJnMlVqZ5Q4Y7K9MYh4KsIXRJ5j05BlAGsZ7nxFiDw2xVCbC7++C4n6y6yjJvyHB3ZRnjUJA1xKDfvCfHAMoixvOcGGtwHD2LSmndT9ZaDZSevJ8slmKAaiPDKApZQxmQY6Q1fcNdpfo5gE8x1mD2xIhMbJuuDCLW+8lCUIV8xIAMoyhZZY3aAZ9aOX7ryy7RPW95sf7pd16l//Gm5+vcUU5TAaCTLI/bMZ63hrm0go5am67sP3RUR06e0a7pbTqwZ6emJseDv9cqjVjvJ/OtKvmIARlGUbLIGrUDvtVqpm0TY3rDCy/WdYeOkUMA6CHr43aM560scUekfdOV5YZb23SlvjTcY3tCfAeudT9ZzZofA55EoRgkHyGOfVmQ4eGRz2SGzVpexxb0R8af9PhyQ9cdOkYOAVRev2NDHsft2M5buRIjInlsusI7cOWRNh+MPUJGPosT44ZeZUDG1yOHAJDs2EC95EqMqLQ2XWnX2nRl4O/JO3ClkTYfjD1CRj6Lk8exBf2R8fXIIQAkOzZQLwNexDCzK83sITM7bmY3+G5PCPLYdIWVvPJImw/GHiEjn8WJcUOvMiDj65FDAEh2bKBeBno7iZmNSHq/pJ+T9LCkI2Z2p3Pu635b5lcem67E+EgddJY2H4w9QkY+ixPjhl5lQMbXI4cAkOzYQL0M90qMF0g67pw74ZxblPRxSa/x3KYgZL3pCit55ZImH4w9QkY+ixXbhl5lQMY3I4cAqi7psaHq9TLUpf6nS/pu278flvRCT20pNVbyqouxR8jIJ8qOjAMANuLYkEyoV2J0GqV1z5Yxs2vMbNbMZk+fPl1Qs8qp6it5RQott4w9+vGZWfKJQYRWZ3sh42iJKbeARGbzxLGhv1AXMR6WdFHbvy+U9Ej7FzjnbnPOzTjnZs4777xCGwcMitwiNmQWsSGziBG5RWzILHwKdRHjiKRLzOwZZjYu6Q2S7vTcJgAAAAAA4FGQe2I455bN7Ncl3SNpRNIfOece8NwsAAAAAADgUZCLGJLknPuUpE/5bgcAAAAAAAhDqLeTAAAAAAAArGPOuf5fFTgzOy3p281//qikH3hsTkjoi/WS9McPnHNXFtGYDbmtOrLaXb++CS2zjCV9EEytJbMDoT/Wa/WH71rLuKyiH1YFU2elXM9pYxxv2jycRLktxSJGOzObdc7N+G5HCOiL9eiPcDE23cXWN7G1Nw9V74PYXn9s7c0b/bFeKP0RSjt8ox9WVaUfYnydtLkY3E4CAAAAAACiwCIGAAAAAACIQhkXMW7z3YCA0Bfr0R/hYmy6i61vYmtvHqreB7G9/tjamzf6Y71Q+iOUdvhGP6yqSj/E+DppcwFKtycGAAAAAAAopzJeiQEAAAAAAEqIRQwAAAAAABAFFjEAAAAAAEAUWMQAAAAAAABRYBEDAAAAAABEgUUMAAAAAAAQBRYxAAAAAABAFFjEAAAAAAAAUWARAwAAAAAARIFFDAAAAAAAEAUWMQAAAAAAQBRYxAAAAAAAAFFgEQMAAAAAAESBRQwAAAAAABAFFjEAAAAAAEAUSrGIceWVVzpJ/OFPFn8KQ275k9GfwpBZ/mT4pxBklj8Z/ikMueVPRn8KQ2b5k+GfREqxiPGDH/zAdxOA1MgtYkNmERsyixiRW8SGzKJopVjEAAAAAAAA5cciBgAAAAAAiIL3RQwzGzGzo2b2v5r/foaZ3Wtm3zSzPzWzcd9tBAAAAAAA/nlfxJB0naQH2/59q6Tfd85dIulfJf2yl1YBAAAAAICgeF3EMLMLJV0l6YPNf5ukl0r68+aXHJT0Wj+tAwAAAAAAIRn1/PPfK+k3JT2l+e8pSf/mnFtu/vthSU/30TD012g41ZdWNDE+ovriiibGRlSrme9moSCMP5IgJwBCRG0qDn2NMpq+4a5UX3/ylqtyakk1ebsSw8xeLemUc+6+9k93+NKOz4s1s2vMbNbMZk+fPp1LG9Fdo+E0N7+ofQdndelNd2vfwVnNzS+q0Uj8eN9KKktuGf/qGCaz5AQ+lKXOIj8h1qay5jbEvkY2yppZxMHn7SQvknS1mZ2U9HGt3kbyXkk/bGatK0QulPRIp//ZOXebc27GOTdz3nnnFdFetKkvrWj/oaM6fGJOyw2nwyfmtP/QUdWXVnw3LWhlyS3jXx3DZJacwIey1FnkJ8TaVNbchtjXyEZZM4s4eFvEcM7d6Jy70Dk3LekNkj7nnPt5SZ+X9H83v2yvpL/y1ET0MDE+oiMnz6z73JGTZzQxPpLrz200nM4uLKvhmh9ZyfcizfgzZtWVVZ0gQwDS6FczfJ3DVFEMfc0xBohPCE8n2eh6SW81s+Na3SPjQ57bgw7qiyvaNb1t3ed2TW9TfTG/lXUuSQxH0vFnzKotizpBhgCkkaRm+DiHqarQ+5pjDBCnIBYxnHNfcM69uvn3E865FzjndjjnXu+cW/DdPmw2MTaiA3t2avf2KY3WTLu3T+nAnp2aGMtvZZ1LEsORdPwZs2rLok6QIQBpJKkZPs5hqir0vuYYA8TJ99NJEKlazTQ1Oa7b984Uttt0DJckVkXS8WfMqi2LOkGGAKSRpGb4OIepqtD7mmMMEKcgrsRAnGo109Yto6pZ82POB6TQL0msmiTjz5hh2DpBhgCkkbRmFH0OU2Uh9zXHGCBOLGIgGqFfkojNGDMMiwwBSIOagTTICxAnbidBNEK/JBGbMWYYFhkCkAY1A2mQFyBOXImBQmT1+KqQL0mMSZGPE2PMMCwyVBweNYikQs4KNSN8IeWHvADx4UqMEms0nOpLK95XlluPr9p/6KiOnDyjXdPbdGDPTk1NjnOg8KDo8Qglh8BGZHM9ajWSKkNWmP/+dMvPtokxPb7cYEwA9MWVGCUV0nOveXxVWIocj5ByCLQjm5tRq5FU7Flh/vvVLT/ziyuMCYBEWMQoqZBOMHh8VViKHI+Qcgi0I5ubUauRVOxZYf771S0/k1tGGRMAibCIUVIhnWDw+KqwFDkeIeUQaEc2N6NWI6nYs8L896tbfo6fOrvuc4wJgG5YxCipkE4weHxVWIocj5ByCLQjm5tRq5FU7Flh/vvVKT/v23OF7vmH7637OsYEQDds7FlSrQPExk2TfJxg8PiqsBQ5HiHlEGhHNjejViOp2LPC/PerU37OHa1pzwt/XIdPnGFMAPTFIkZJhXaC0Xp8laS1j/CnqPEILYdAC9nsjFqNpGLOCvPfv075YUwAJBXXUQepxHyCgfIghwgV2QSqi/kfHsYEQFLsiZGhRsPp7MKyGq75kcdCoWKYAygjcg2EjTmaH/oWQIhY5sxI65njG++vnJocL/xSuEbDqb60wuV4FRHKeIc0B4CspM11KPMRyFqo2ebYk5+i+zbUjAEID1diZCSUZ463Djj7Ds7q0pvu1r6Ds5qbX2TlvKRCGu9Q5gCQpTS5Dmk+AlkKOdsce/JTZN+GnDEA4WERIyOhPHO8LAdzLl9MJqTxDmUOhIIMl0OaXPuaj2QNeSsi24PmmGPPk7KuBUX2bUjnMwDCxyJGRkJ55ngZDuasxicX0niHMgdCQIbLI02ufcxHsoYi5J3tYXLMsWdVHrWgyL4N6XwGQPhYxMhI65nju7dPabRm2r19ysvzrctwMGc1PrmQxjuUORACMlweaXLtYz6SNRQh72wPk2OOPavyqAVF9m1I5zMAwsfGnhkJ5ZnjrQPOxk2YYjqYsxqfXEjjHcocCAEZLo80ufYxH8kaipB3tofJMceeVXnUgiL7NqTzGQDhYxEjQyE837oMB/PWavzhE3Nrn2utxvPc8PVCG+8Q5kAIyHC5JM21j/lI1lCEvLM9bI459uRXC4rq29DOZwCEjdtJSqh1wKlZ82NkBwAuDU0n9vEuIzJcXUXPR7KGouSZbXI8vDL0IeczAJKq5nI1gsZqPGJHhlEUsoYyIMfDow8BVAmLGAgSl4YidmQYRSFrKANyPDz6EEBVcDsJAAAAAACIAosYAAAAAAAgClxrBgAAAABATqZvuCv1/3PylqtyaEk5cCUGAAAAAACIAosYAAAAAAAgCt4WMczsIjP7vJk9aGYPmNl1zc9vM7PPmNk3mx9/xFcbsVmj4XR2YVkN1/zYcL6bBHREVoHsMJ8QE/KKQZAbIB4+r8RYlvQbzrl/L+knJV1rZs+UdIOkv3HOXSLpb5r/RgAaDae5+UXtOzirS2+6W/sOzmpufpEij+CQVSA7zCfEhLxiEOQGiIu3RQzn3Pecc19p/v0xSQ9Kerqk10g62Pyyg5Je66eF2Ki+tKL9h47q8Ik5LTecDp+Y0/5DR1VfWvHdtI5YUa+uJ5ZXNL+wrI/+lxfqrv0/pfOesiXorAJ5yKoGxlb7EYe8jtHktZqGzRO5AeISxNNJzGxa0k5J90p6qnPue9LqQoeZnd/l/7lG0jWSdPHFFxfT0IqbGB/RkZNn1n3uyMkzmhgf8dSi7lor6vsPHdWRk2e0a3qbDuzZqanJcdVq5q1d5DZ/jYbT/MKybvzk19bG/tbXXa73fOahILMaOjIbpyxrYEy1XyKzMcjzGB1bXlvI7eCyyFOsufGJzMIn7xt7mtlWSXdIeotz7tGk/59z7jbn3Ixzbua8887Lr4FYU19c0a7pbes+t2t6m+qL4a1Sh7qiTm7ztzr2x9aN/fV33K+3vOzSILMaOjIbpyxrYEy1XyKzMcjzGB1bXlvI7eCyyFOsufGJzMInr4sYZjam1QWMjznnPtn89PfN7ILmf79A0ilf7cN6E2MjOrBnp3Zvn9JozbR7+5QO7NmpibHwVqlZUa+ubmN/8dREkFkF8pBlDYyp9iMOeR6jyWv1ZJEncgPExdvtJGZmkj4k6UHn3Hva/tOdkvZKuqX58a88NA8d1Gqmqclx3b53RhPjI6ovrmhibMTr7RndtFbUD5+YW/tca0V965Yg7qJCTrqO/cKKtp7D2KMasqyBMdV+xCHPYzR5rZ4s8kRugLj4vBLjRZLeJOmlZnas+edVWl28+Dkz+6akn2v+G4Go1Uxbt4yqZs2PgRZ3VtSrq+vYcxUOKiTrGhhL7Ucc8j5Gk9dqySpP5AaIh7e3JZ1zX5LUrTr8bJ4/u9Fwqi+tsNJaYqyob1aV3DP2CImvecc8QNHSZJ18Ikuh5akq51uAT5W7tjrUp1YkRWFMrrWiLqkyt5B0y0fsuU+rimOP8Pied2nmAccWDGOQrHfKJzlMjr5aL5Tjvu+6D1SF96eTFC3Up1Yk0SqM+w7O6tKb7ta+g7Oam1/M7NnqiFuvfMSceyBWscw7ji0YVhZZJ4fJ0VfhiqXuA7Gr3CJGzE+toDCil175iDn3QKximXccWzCsLLJODpOjr8IVS90HYle5RYyYnwNNYUQvvfIRc+6BWMUy7zi2YFhZZJ0cJkdfhSuWug/ErnKLGDE/tYLCiF565SPm3AOximXecWzBsLLIOjlMjr4KVyx1H4hd5Xa8C20H4zRahXHjZkEURki98xFz7oFYxTLvOLZgWFlknRwmR1+FK5a6D8SucosYUjg7GKdFYUQv/fIRa+6BmMUw7zi2IAvDZp0cJkdfhS2Gug/EjpkVGQojeiEfAAZB7UAIyGFy9BWAKqvcnhgAAAAAACBOLGJAjYbT2YVlNVzzY8bPGc/7+2NwjE326NPs0Jf90UdxK9P4lem1hKyq/VzV1w2gM64/q7hGw2lufnHT5lBTk+Pr7q1sNJzqSyup771M+v3R36Bj0Ov7MTbZok+zE1pfZj3/smpTSH1UVRwfy/VaQlaGfh5kvpThdQPIFldiBCLNCnOWq9H1pRXtP3RUh0/MabnhdPjEnPYfOqr60pOP6WodPPYdnNWlN92tfQdnNTe/mOjnJvn+6G+YMej2/eYXl7Vtclw3X/0sveo5FzA2Geia98UV3kFKyVft6FRfs55/WemVNxSD4+OqYV/Lunn3xLLqi9TLTorITJ5XPAw6X8owV7iSBMgWixh9FFF00hT1rE+mJ8ZHdOTkmXWfO3LyjCbGn3xM1zAHjyTfH5ttzF19MbsDeCtD13zkPl32jrt1850P6G0vv0xXP/dpjM2QuuZ9y0hwvwCHzkft6FZfn1gu7gQ6zTGnV97IVzGqenzcmNNhXsumefeRWZ2ZX9Rb//QY9XKDvDOT94LtoPMl5rkiZduvLIYAq1jE6KGod9/SFPWsV6PriyvaNb1t3ed2TW9b907eMAePJN8f63XK3cSW7A7gnTJ0/R3369qX7GBshtQt79+Zq0f9DpIPPmpHt/raaKiQE+i0x5xeeSNfxaji8bFTTs8+sTzwa+k0797+ifv1az+zg3q5Qd6ZyfuKh0HnS6xzpSWrfg31qkDABxYxeijq8rU0RT3r1eiJsREd2LNTu7dPabRm2r19Sgf27NTEWNuVGEMcPJJ8f6zXKXffmatndgDvlqEd529lbIbUOe9X6L2f/ca6r4vpHSRffNSOXlc2FHECnfaYs9pHV6zro1tfd7ne+9lvkK+CVPH42CmnH/67b+l9G7KY9LX0Oia1/k6eV+WdmbyveBh0vsQ6V1qy6tcy3FYDZIWNPXso6vK1VlE/fGJu7XOtor7x2d9pvjaJWs00NTmu2/fOdN1kqXXw2LihUpKDR5Lvj/U65e69n/2GDuy5QvsPHUs9Bht1z9Aym2QNqVPeayZ9/9GFdV83zJytCh+1o+vcWFgZuAamkfaYU6uZJreM6nf/03N00bYJHT91Vu/+9EM6/dgC+SpIFY+PnXJ64HPHde1Ldwz0WrrNu+Onzq79nTyvyjszWZ9jbjTofIl1rrRk1a+x31YDZIkjQg95F/OWNEV9mBOmbmo1W3s9nV7XsAePft8f63XK3fcfXdDkltFMDuDdMjQ5PhrNCUHINua90XCF/AJcRkXXjq71dXxEE+MjuZ9AD3LMOWd0RJNbRvXGD95Lvjyo4vGxW04fX2oM9Fo6zbt3vf5yvfueh6J7x70IeWYmj3PMdsPMlxjnSktW/VrU7yVADMy5+O+jmpmZcbOzs5l/3yIf6ZTmkVMhPuqvRArryG65LSJ3ZKhYOfe398yWic+5Mejcj3Q+F9LAKmS2aHkco9ZleGFFtZp0zlhwea5ErY20ngQvi34dYO5VIrO+TN9wV+4/4+QtV+X+MwKUKLcs2/VQ5OVraVaYY16NRn9F5I4MFYv+jofPsRp07pMvFCmPY9S6DJ/zZIbJc/GoJ/nIol9jv60GyBLVqQ+KOXwgd0A1MfcRA3IK+MHcA1bxdBIAAAAAABAFlvAAAAAAAEEZZN+Jiu4jUTlciRGARsPp7MKyGq75sRH/ZqtFoN+SCa2fQmsPgO56zdcyzuUyviaf6E/EKG1uyTlQPK7E8KzIJ6CUCf2WTGj9FFp7AHTXa75KKt1cpj5li/5EjNLmlpwDfqS6EsPM/oOZvdXMXp5Xg4rme/W0vrSi/YeO6vCJOS03nA6fmNP+Q0dVX1optB2xod+S8dFPveYU44YkfNdlrOo1X8s4l8v4mnwquj+pG+nRZ5ulzS11A/Cj5yKGmf1929/3SfoDSU+R9NtmdkPObctda/V038FZXXrT3dp3cFZz84uFFvGJ8REdOXlm3eeOnDyjifGRwtoQI/otmaL7qd+cYtzQTwh1Gat6zdcyzuUyviafiuxP6kZ69FlnaXNL3QD86Hclxljb36+R9HPOuf8q6eWSfj63VhUkz9XTpKvb9cUV7Zretu5zu6a3qb7ICm4v9FsyRfdTvznVrz28K1R+/caYd7XC0Wu+lrEGl/E1+dTen1c/92m65y0v1kP//ZWaz6G2Uzc648rI9NLWAeoG4Ee/RYyamf2ImU1JMufcaUlyzs1LWs69dTnLcvW0/UBRX1zW3PxCotXtibERHdizU7u3T2m0Ztq9fUoH9uzUxBgruL1Uvd+S/rJfdD/1m1O92sO7QuWXZIx5Vyu5vBf9es3XstTg9j6Ukz7wxudF/5pC0crIW192id728st0850P6LJ33K1rPnJf5rWdurFZzFdG+nxDI21tK0stBGLTb2PPfyfpPkkmyZnZjznn/sXMtjY/lxszu1LS+ySNSPqgc+6WrH9Ga/X08Im5tc+1Vk+3bkm+5+nGTX0++9af1o2f/Nra922tbt++d2bT963VTFOT47p974wmxkdUX1zRxNgImwH1UeV+S7OJVNH91G9O9WrP2YXltXeFpN7zBnFqf+dP6jzGWdXlsitiM7l+9SP2Gty5D6/Qh35hRueMxfmaQtLKzy/+h2fomo/cl2ttp25s1q/ehtpnvjfKTHveVOXzUcCnnldiOOemnXPbnXPPaH78l+Z/akj6j3k1ysxGJL1f0islPVPSHjN7ZtY/J6vV042X5F20bSLV6natZqu/4Jmt/aKH/qrab2kvAS2yn5LMqW7tCfldIWQjyRjzrlYyRV0K3qt+xF6DO/fhMTWcon36jvS6AAAbfElEQVRNoanVTJNbRnOv7dSNzYa5MtKnEG5zSVvbYq+FQIwGWmp1ztUlfSvjtrR7gaTjzrkTkmRmH5f0Gklfz/KHZLV6uvFAcfzU2SBXt1EOIf+yP8ycCvVdIWQnyRjzrlYyIdeBWNCHxSiitlM3NhvmykifmJcAkkj1iNUCPV3Sd9v+/XDzc5nLYvV046Y+7//8cf3e//PcDavbV3hf3e6EjRTjU6ZNpNrzVzPpwJ4rgntXCNlJ+s4f72r1l3UdGPZYEOOxJJRaWva+L+odf+rGesNcGelLo+E0v7Csh/77K3XPW16sq5/7NEnFzsvQ5xOAVaG+vdmpiq6rImZ2jVafmKKLL764iDZ11TpQtO7f23HepCbGR/S7/+k5umjbhL57pq7xkfDWixoNp8eeWNK/1pd00bYJPfb4kkzSuQGtyJdNFrndmLfW/aJZnBA2Gk71pZWB35VJcy9rp6/9wBufp9vfPKOJLcVmcNjXXWZZ1tpQ3/mLUZo60C/fw9yD3mi41e+5ZUQ/eGxB7/3sN/T9RxcKvYd9o6SZTVtL86gTG/t+/0t36Bde9AxtPWc00c/wvX9AEsz7ZLI+rw2p35PMnU5ZvvV1l2vHeZPa88IfL+QNjazmU1XOKUL6XQzVY86Ft8JoZrsl3eyce0Xz3zdKknPudzt9/czMjJudnS2whZu1F6z5heV1m1hJ0u7tU8FtUFhfXNaZ+UW9/RP3rxXrd73+cr37noe8n4SmkfHBorAXO0xuiziZHuTgfXZhWfsOzibKfpqvzUK3Povhl4A+osgssjfoLwYb8512Lrb/3LNPLOvDf/ctHfjc8bVfOt796Yd0+rGFfnO5kNz2y2zSWppXnWjv+6uf+zS97eWX6fo77k/8M5KOXVV+qcoZtXYASedOtyzf9ubna3K8mKtEhj0vaTScnlhe0fzCsvYfOhbCOUX0mZ2+4a7U/8/JW67KvB2dDNK2tIp6LYFJlNvwLg9YdUTSJWb2DDMbl/QGSXd6blNP7ZfkFbGJVRYaDentn7h/3eZJb//E/fq1n9kRzfPCq/pYzjwuAc1iM60097IWed9rr5yEsIkYMIgkdSBJvtPMxY1z6Vf+5D69dueFetVzLtDhE3O6/o77de1LdgR5zOskaS3Nq0609/21L9mh6++4P9XPSDJ2VT1OIgxJ5063LE8WeJvLMOclrXl26tEF7T90jHMKIGdBLmI455Yl/bqkeyQ9KOnPnHMP+G1VcqHcZ9vPxJbOxXrH+VvX/h76SSi/gGYni0WFNNkvcp70ygmbiKHMkuQ71bztMJdaCxet773j/K1BHvOGkVedaO/7HedvTf0zkowdx0n4lHTuhHDuPEwbWvMs7RMKAQwmyEUMSXLOfco5d6lz7iecc+/03Z40Qn1s1Ub1hc7F+vips2t/D/0klF9As5PFCUSa7Bc5T3rlJIQTJyAvSfKdat52mUutxe9d09v03TP1II95w8irTrT3fevJZml+RpKx4zgJn5LOnRDOnYdpQ2ueDTKPAaQXzgYNJRLSZkq9TIyP6MCeK9bdt9faEyPUhZeNeCxndrLYMDRN9oucJ71ykudGqYBvSfKdZi52m0vHT51dexLX5JZRnTMa3jFvGHnVifa+P3espvftuULXbbiXvtfPSDJ2HCfhU9K5E8K5cxaPiX//54/r1tddvmlvG84pUCYh7FUS5MaeaZVpA6Sirdvsa2FFtZp0zli4Cy8b5bDZWvSbIA2jrJu/9ctJ5K+70plFf1nmu9Ncet+eKzQ1Oa7HlxppvncQG3umUUSdCHXTZkii1g4s8mNsIu3z7Kk/tEVvedmlunhqQvWF1dft6fVGn9kQflnupsobe+Y8LolyyxJ8hXQ7iLTeidl6zpNxiOXdmRBW7stkXR4iyUAS/XLi+3WX5QSvLK+jbLLMd6+5tHVLsHeoZqKIOpHHz/BxnKQWoF0VjrGd5pnc+nNrANlhZlVEmd+J8X1wRBxCzUlZ5mZZXgf6C3Uuobsix4xagJAUmUdqI1Cccr9tgjXsTg6EqSxzsyyvA8BwqAUICXkEyolFjIqo6u7kjYbT2YVlNVzzYyP+PWBQLmWZm6G9DuY+yiiGXIdWC7BeDBnKEnkEyolFjIqo4mMkW5cQ7js4q0tvulv7Ds5qbn6x9AdsxKPRcDr7xHIp5mZINYa5jzKKJdch1QKsF0uGskQegXJiEaMiQnj+dtG4hBChqy+t6MN/9y3d+rrL183N9+25Irq5GVKNYe6jjGLJdUi1AOvFkqEskUegnNh1JhLD7qxcxad4cAkhQtFt/k6Mj+jA547r+Ol53Xz1s7Tj/K06fupslBvghVRjsp77PGkBIYjlmNZeC84dq6m+uKLJLaPMnQCEkKGi62lIxyYA2eFKjAhkdflfa9fkmjU/lryAcwkhQtBr/rYyeudXH9Er3vtF/cRvfUo33/mAHl9q+G72QEKpMVnO/Spefo0wxXRMq9VME2MjOjO/pGs+ch9zJxC+M+SrnoZybAKQHRYxIlDFy/+ywCWECEGv+UtG85Flv1J/EYrY6gVzJzy+M0QmAGSF20kiEMLlfzHiEkKEoNf8rRkZzUOWc5/6i1DEdkxj7oTHd4bIBICscCVGBHxf/hczLiGEb/3mLxnNR1b9Sv1FSGKqF8ydMPnMEJkAkBUWMSLg+/I/AINj/saN8QMGw9zBRmQCQFa4nSQCvi//AzA45m/cGD9gMMwdbEQmAGSFRYxItC7/k7T2EUAcmL9xY/yAwTB3sBGZAJAFqgcAAAAAIFfTN9zluwkdhdquosT4+tkTAwAAAAAARIFFDAAAAAAAEAUWMQAAAAAAQBRYxPCk0XA6u7Cshmt+bDjfTQLWIaPIE/lCTMgrgLxRZ4Dk2NjTg0bDaW5+UfsPHdWRk2e0a3qbDuzZqanJcR4zhSCQUeSJfCEm5BVA3qgzQDpcieFBfWlF+w8d1eETc1puOB0+Maf9h46qvrTiu2mAJDKKfJEvxIS8AsgbdQZIh0UMDybGR3Tk5Jl1nzty8owmxkcKawOXrKGXEDKaB3IfhrT5YtzgQyt3E+MjuvnqZ+nq5z5t7b+VoR6i2qirYSnreReQFxYxPKgvrmjX9LZ1n9s1vU31xWJWW1uXrO07OKtLb7pb+w7Oam5+kQMY1vjOaB7IfTjS5Itxgw8bc3fznQ/obS+/bG0hI/Z6iGqjroanjOddQJ5YxPBgYmxEB/bs1O7tUxqtmXZvn9KBPTs1MVbMaiuXrKEf3xnNA7kPR5p8MW7woVPurr/jfl37kh2lqIeoNupqeMp43gXkiY09PajVTFOT47p974wmxkdUX1zRxNhIYRv3cMka+vGd0TyQ+3CkyRfjBh+65e6Sp25dzW3k9RDVRl0NTxnPu4A8cSWGJ7WaaeuWUdWs+bHAIhXTJWvcs+mPz4zmoVvun1haIWMeJM1XnvWK+oJueuWuiHpINpGnos4DyXE6ZTvvAvLEIkYFxXLJGvdsIkudcv+BNz5P8wvLZCxgedUr6gt68XmcJJvIWxH5JscA8uTldhIze5ek/0vSoqR/kvSLzrl/a/63GyX9sqQVSfudc/f4aKNvjYZTfWll9ZKyhRXVatI5Y9lcXhbLJWvt92xKWrtn8/a9M9q6hTuhkN7klhHd/uYZTWxZnVeStP+jXyksY+vmdaDzLjR51atY6ouPzJDTVRvrxcR4un4YtB9jySbi1Mrltskx3fbm52tyy2gu8zykHFPTgPLxdTT8jKQbnXPLZnarpBslXW9mz5T0BknPkvQ0SZ81s0udc+Hd55Cj1ur1/kNHdeTkGe2a3qZ3vf5yvfueh/T9Rxd0YM9OTU2OD72Q0TqIhHpSxD2byEqnOXVgz05NbR0vLGNd2zDkXK6CPOpVDPXFR2bIafc+SJONYfoxhmwiTkXO71ByTE0DysnL7STOuU8755ab//yypAubf3+NpI875xacc9+SdFzSC3y00adOu0a//RP369d+ZkeldpCOae8OhK3bTuzzC8uFZYzd4MMSQ33xkRlymk0fDPM9Ysgm4lTk/A4lx9Q0oJxCeAv+lyT9afPvT9fqokbLw83PVUq31esd529d+3sV3pFp3bO56d2wwPbuQPh6vSNUVMZCeVcKq2KoLz4yQ06z6YNhvkcM2UScipzfoeSYmlY90zfc5bsJmSnTa8labosYZvZZST/W4T/d5Jz7q+bX3CRpWdLHWv9bh6/vuAOQmV0j6RpJuvjii4dub0haq9et+wil1dXr46fOrv29tUN6mcWyd0caZc5tyLrNqceXGoVlrFsbQp/LZc1sDPXFR2ZizWm7YTObRR8M8z1iyCayV0StLXJ+h5LjMtS0UJX1/ABxyO12Eufcy5xzz+7wp7WAsVfSqyX9vHOutVDxsKSL2r7NhZIe6fL9b3POzTjnZs4777y8XoYXnXaNftfrL9cffuF4sE8SyUvZHjdV5tyGrNdO7EVlLJanAm1U5syGXl98ZCbWnLYbNrNZ9MGw3yP0bCJ7RdTaoud3CDkuQ00LVZnPDxA+e3L9oMAfanalpPdI+mnn3Om2zz9L0v/U6j4YT5P0N5Iu6bex58zMjJudnc2xxcXL8+kk6Kmwji1jbkMWwu7kObWBzJZYiZ9OUkhuB81sFn0QQs1BpkpRa6uYyyq+5qbgMsvtEdV18parkn5potz6uo7qDyRtkfQZM5OkLzvnftU594CZ/Zmkr2v1NpNrq/ZkkpZ1u/Gf8+QwcekbMJgQnsgTQhsQFx+ZIafZ9AH9iBBVMZdVfM1A2XmZyc65HT3+2zslvbPA5gAAAAAAgAh4ecRq0RoNp7MLy2q45sdG71to0n49EAJyGx/GbDP6JByMRXfD9A39ijIgx+nQX0C2Sn9NVaPhNDe/uOkRT1OT4x3vh0v79UAIyG18GLPN6JNwMBbdDdM39CvKgBynQ38B2Sv9lRj1pRXtP3RUh0/MabnhdPjEnPYfOqr6UuetNtJ+PRACchsfxmwz+iQcjEV3w/QN/YoyIMfp0F9A9kq/iDExPqIjJ8+s+9yRk2c0Md750Uppvx4IAbmND2O2GX0SDsaiu2H6hn5FGZDjdOgvIHulX8SoL65o1/S2dZ/bNb1N9cUuV2Kk/HogBOQ2PozZZvRJOBiL7obpG/oVZUCO06G/gOyVfhFjYmxEB/bs1O7tUxqtmXZvn9KBPTs1MdblSoyUXw+EgNzGhzHbjD4JB2PR3TB9Q7+iDMhxOvQXkD1zLv7dcWdmZtzs7GzX/95oONWXVjQxPqL64oomxkZ6bqST9utRKoUNdL/cpkVu45PRmEWb2U7IcThyHotCBjWvzA7TN2Q8WqWqtcMix+l46q/gMjt9w10FtAYhOnnLVUm/NFFuS/90Ekmq1Uxbt6y+1NbHLL8eCAG5jQ9jthl9Eg7Gorth+oZ+RRmQ43ToLyBbpb+dBAAAAAAAlAOLGAAAAAAAIAosYlRIo+F0dmFZDdf82Ih/PxSgDJib6dBfKAuyDKAdNQFIhpuyKqLRcJqbX9T+Q0d15OQZ7ZrepgN7dmpqcpyNmACPmJvp0F8oC7IMoB01AUiOKzEqor60ov2HjurwiTktN5wOn5jT/kNHVV/iGdWAT8zNdOgvlAVZBtCOmgAkxyJGRUyMj+jIyTPrPnfk5BlNjOf7jGouiwN66zU3mTeb+aplIaCehiOLsahyloG0qlD/qAlAcixi5CDEQltfXNGu6W3rPrdrepvqi/mt7rYui9t3cFaX3nS39h2c1dz8YhD9gfILcR520m1ufmeuXup5M+j4+KhlIaCehiOrsagvrmj/S3fonre8WP/0O6/SPW95sfa/dEfpswy0JD0OVKX+VfX4BgyCRYyMhVpoJ8ZGdGDPTu3ePqXRmmn39ikd2LNTE2P5re5yWRx8CXUedtJpbr7r9ZfrPZ/5RmnnzTDj46OWhYB6Go6sxuLc0Zre8IKLdfOdD+iyd9ytm+98QG94wcU6d5RTM5RfmuNAVepfVY9vwCDY2DNj7YVW0lqhvX3vjLZu8dfdtZppanJct++d0cT4iOqLK5oYG8l1oyAui4Mvoc7DTjbNzYUVveMvv6Y7v/rI2teUbd4MMz4+alkIqKfhyGosHl9u6LqPH1s3D677+LHVeTDCQgbKLc1xoCr1r6rHN2AQHCUzFnKhrdVMW7eMqmbNjzkXRS6Lgy8hz8NO2uemTPr+owvr/nvZ5s2w41N0LQsB9TQcWY1FbHUKyFKa/Fep/lXx+AYMgkWMjFWp0PbDZXHwJeZ5WIV5E/P4+FKFXMQiq7FgHqDK0uSf+gdgo7Cuqy6BVqHd+IznKhZaLouDLzHPwyrMm5jHx5cq5CIWWY0F8wBVlib/1D8AG7GIkTEK7Xqty+IkBbcXAcor9nlY9nkT+/j4UvZcxCSLsWAeoMrS5p/6B6AdVSAHFFrAP+Zh2BgfgHmAaiP/AAbFnhgAAAAAACAKLGIAAAAAAIAosIgBAAAAAACiwCIGAAAAAACIAosYAAAAAAAgCuac892GoZnZaUnfbv7zRyX9wGNzQkJfrJekP37gnLuyiMZsyG3VkdXu+vVNaJllLOmDYGotmR0I/bFeqz9811rGZRX9sCqYOivlek4b43jT5uEkym0pFjHamdmsc27GdztCQF+sR3+Ei7HpLra+ia29eah6H8T2+mNrb97oj/VC6Y9Q2uEb/bCqKv0Q4+ukzcXgdhIAAAAAABAFFjEAAAAAAEAUyriIcZvvBgSEvliP/ggXY9NdbH0TW3vzUPU+iO31x9bevNEf64XSH6G0wzf6YVVV+iHG10mbC1C6PTEAAAAAAEA5lfFKDAAAAAAAUEKlWcQwsyvN7CEzO25mN/huj29mdtLMvmZmx8xs1nd7imZmf2Rmp8zsH9o+t83MPmNm32x+/BGfbcSqqme1Xey5rXodrmKWY85s1fPaSRUz3C7UPJPVVVXNZ6i5zIuZvcvM/tHM7jezvzCzH25+ftrMHm+O/zEz+4DvtraLYZ6a2UVm9nkze9DMHjCz65qfv9nM/rmtb1/lu639lGIRw8xGJL1f0islPVPSHjN7pt9WBeElzrkrYntkTkY+LGnjM4ZvkPQ3zrlLJP1N898IQ5Wz2u7DijS31OE1VcvyhxVhZslrT1XLcLsPK7A8k9VNqpjPDyuwXObsM5Ke7Zy7XNI3JN3Y9t/+qTn+VzjnftVP8zaLaJ4uS/oN59y/l/STkq5ta+fvt/Xtp/w1MZlSLGJIeoGk4865E865RUkfl/Qaz22CR865L0o6s+HTr5F0sPn3g5JeW2ijgD4izy11uIIizix5xSaB5pmsVlygucyNc+7Tzrnl5j+/LOlCn+1JKIp56pz7nnPuK82/PybpQUlP99uqwZRlEePpkr7b9u+HFemAZMhJ+rSZ3Wdm1/huTCCe6pz7nrQ6iSWd77k9WEVWe4slt9RhstwSQ2bJa2dkeDPfeSarTyKfT/Kdy6L8kqS72/79DDM7amZ/a2Y/5atRHUQ3T81sWtJOSfc2P/XrzVt4/iiG25NGfTcgI9bhc1V/7MqLnHOPmNn5kj5jZv/YXMkFQkNWy4E6TJZjQl47I8PhIatPIp8lYWaflfRjHf7TTc65v2p+zU1avf3hY83/9j1JFzvn5szs+ZL+0sye5Zx7tJBG9xbVPDWzrZLukPQW59yjZvaHkv6bVtv83yT9nlYXkIJVlisxHpZ0Udu/L5T0iKe2BME590jz4ylJf6HVy5yq7vtmdoEkNT+e8tweiKwmEEtuK1+HyfKaGDJb+bx2QoY78p1nstpEPtfxncuhOOde5px7doc/rQWMvZJeLennnXOu+f8sOOfmmn+/T9I/SbrU12vYIJp5amZjWl3A+Jhz7pOS5Jz7vnNuxTnXkHS7IphbZVnEOCLpEjN7hpmNS3qDpDs9t8kbM5s0s6e0/i7p5ZL+off/VQl3Strb/PteSX/lsS0QWU0oltxWug6T5XViyGyl89oJGe7Kd57JqshnB75zmRszu1LS9ZKuds7V2z5/XnMDTZnZdkmXSDrhp5WbRDFPzcwkfUjSg86597R9/oK2L/uPimBuleJ2Eufcspn9uqR7JI1I+iPn3AOem+XTUyX9xWpONSrpfzrn/tpvk4plZock/YykHzWzhyX9tqRbJP2Zmf2ypO9Ier2/FqKp8lltF3NuqcPVzHKsmSWvHVUyw+1CzDNZXVPZfIaYy5z9gaQtWr1lSJK+3HwSyYsl/X9mtixpRdKvOuc2bnjqRUTz9EWS3iTpa2Z2rPm539Lq01Su0OrtJCcl/Yqf5iVnzSt0AAAAAAAAglaW20kAAAAAAEDJsYgBAAAAAACiwCIGAAAAAACIAosYAAAAAAAgCixiAAAAAACAKLCIUQFmdqWZPWRmx83sBt/tAfoxsz8ys1NmFvxzqgFJMrOLzOzzZvagmT1gZtf5bhPQi5mdY2Z/b2ZfbWb2v/puE5CEmY2Y2VEz+1++2wIkYWYnzexrZnbMzGZ9t6cMeMRqyZnZiKRvSPo5SQ9LOiJpj3Pu614bBvRgZi+WdFbSR5xzz/bdHqAfM7tA0gXOua+Y2VMk3SfptdRahMrMTNKkc+6smY1J+pKk65xzX/bcNKAnM3urpBlJP+Sce7Xv9gD9mNlJSTPOuR/4bktZcCVG+b1A0nHn3Ann3KKkj0t6jec2AT05574o6YzvdgBJOee+55z7SvPvj0l6UNLT/bYK6M6tOtv851jzD+9sIWhmdqGkqyR90HdbAPjDIkb5PV3Sd9v+/bA4sQaA3JjZtKSdku712xKgt+Zl+ccknZL0GeccmUXo3ivpNyU1fDcESMFJ+rSZ3Wdm1/huTBmwiFF+1uFzvNMCADkws62S7pD0Fufco77bA/TinFtxzl0h6UJJLzAzbt9DsMzs1ZJOOefu890WIKUXOeeeJ+mVkq5t3jaNIbCIUX4PS7qo7d8XSnrEU1sAoLSa+wrcIeljzrlP+m4PkJRz7t8kfUHSlZ6bAvTyIklXN/cX+Likl5rZR/02CejPOfdI8+MpSX+h1dv9MQQWMcrviKRLzOwZZjYu6Q2S7vTcJgAoleYmiR+S9KBz7j2+2wP0Y2bnmdkPN/9+rqSXSfpHv60CunPO3eicu9A5N63V89nPOefe6LlZQE9mNtnc8FtmNinp5ZJ4+t6QWMQoOefcsqRfl3SPVjea+zPn3AN+WwX0ZmaHJB2WdJmZPWxmv+y7TUAfL5L0Jq2+M3is+edVvhsF9HCBpM+b2f1afcPjM845HlkJANl6qqQvmdlXJf29pLucc3/tuU3R4xGrAAAAAAAgClyJAQAAAAAAosAiBgAAAAAAiAKLGAAAAAAAIAosYgAAAAAAgCiwiAEAAAAAAKLAIgYAAAAAAIgCixgAAAAAACAKLGIAAAAAAIAo/P8fGIVUGg8X0gAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 1080x1080 with 42 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "model.pairplot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Cook's distance plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\programdata\\miniconda3\\lib\\site-packages\\matplotlib\\cbook\\deprecation.py:107: MatplotlibDeprecationWarning: stem() got an unexpected keyword argument 'use_line_collection'. This will raise a TypeError in future versions.\n",
      "  warnings.warn(message, mplDeprecation, stacklevel=1)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "model.cook_distance()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Influence plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "model.influence_plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Variance inflation factors"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Variance inflation factor for feature 0: 5.03\n",
      "Variance inflation factor for feature 1: 3.84\n",
      "Variance inflation factor for feature 2: 3.68\n",
      "Variance inflation factor for feature 3: 2.73\n",
      "Variance inflation factor for feature 4: 3.33\n"
     ]
    }
   ],
   "source": [
    "model.vif()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Generate all diagnostics plots with `run_diagnostics`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "The residuals seem to have come from a Gaussian process\n"
     ]
    }
   ],
   "source": [
    "model.run_diagnostics()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Test `predict` with new samples"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "num_samples=20\n",
    "num_dim =5\n",
    "X_test = 10*np.random.random(size=(num_samples,num_dim))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([-30.1283978 , -17.94973418,  18.97708482, -15.17951234,\n",
       "        -3.25066473, -11.90628862, -17.57582617,  12.81152568,\n",
       "        -1.9615583 ,  25.67017197,   4.33227393, -23.45401895,\n",
       "        20.68458566,  19.56289471, -10.43957454, -14.86038328,\n",
       "        -7.86502117,  18.12864317,  -3.77303316,  13.47824212])"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.predict(X_test)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Ingest data, fit model, and plot visual diagnostics in a loop\n",
    "This is the big advantage of OOP. Once you have compact representation of your class, you can call methods and visualize for a lot of cases, on a continuous loop.\n",
    "\n",
    "Here, we are increasing the noise level of the data, fitting model, and plotting the Q-Q plot."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Simulating a regression problem...\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Simulating a regression problem...\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Simulating a regression problem...\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Simulating a regression problem...\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "num_samples=50\n",
    "num_dim = 15\n",
    "X = np.random.random(size=(num_samples,num_dim))\n",
    "coeff = np.random.randint(-10,10,num_dim)   \n",
    "m = mlr()\n",
    "\n",
    "for i in range(5,21,5):\n",
    "    print(f\"\\nSimulating a regression problem...\")\n",
    "    y = np.dot(coeff,X.T)+i*np.random.normal(num_samples)\n",
    "    m.ingest_data(X,y)\n",
    "    m.fit()\n",
    "    m.qqplot_resid()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
